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Creating a data-driven business at McKinsey & Co.

Mike Wright, Global CIO, is turning knowledge into value at the global management consulting firm.

Mike Wright, Global CIO, McKinsey & Co.

When your greatest asset is the knowledge of your people, how do you keep track of who knows what? Mike Wright, CIO of McKinsey & Company since 2013, uses a combination of artificial intelligence (AI), a simplified architecture, and a user-centric design to turn data into client-relevant value at one of the world’s leading global consulting firms.

I recently spoke with Wright about how he is creating a data-driven organization and, just as importantly, how he is changing the culture of the IT organization to support it. What follows is an edited transcript of that conversation.

Martha Heller: What does “digital” mean to McKinsey?

Mike Wright: We look at “digital” primarily from a business lens – i.e. as a new capability to allow us to do what we’ve been doing for decades: helping our clients make substantial lasting improvements while attracting and retaining outstanding people. While “digital” does not change our two-part mission, it does give us the opportunity to reimagine how we deliver it. For instance, we can eliminate and automate processes and we can use data to personalize the experience for our clients and our people.

How are you using data to improve the customer and employee experience?

We aspire to bring the best of McKinsey to every client. To do that, we need to take advantage of the knowledge that exists across our 17,000 consultants in 66 countries. Historically, we’ve had a central knowledge repository. Now we are asking: how do we expand that repository to include a much greater variety of formats, like video and audio files, code snippets, and data sets, with better curation and search? How do we allow our clients and employees to access validated external resources in addition to our internal knowledge?  As a large firm, we run the risk of losing our grip on that knowledge. Digital helps us counter these scale and geographic distance challenges, and ensure we remain personal to our people and relevant to our clients.

What is the technology you are using to provide that data?

The data is held in relational and graph databases with very good tagging and semantic search capabilities. We also use AI and machine learning techniques to bolster our cognitive capabilities. But it is not the technology that improves the client and employee experience, it’s the data. When you don’t get the answers you need, it is because we have not properly codified or tagged the data and we have not enabled the right search and retrieval capabilities.

How are you overcoming that data challenge?

We know that there are four keys to creating a data-driven organization:

  • Hire the right people – namely, those who understand the value and relevance that data brings to our clients.
  • Understand what data is most important to our customer experience.
  • Use artificial intelligence, machine learning and other tools to augment the power of human curation to make it a really great experience. At McKinsey, we are encouraging people to take ownership of their data, so that the knowledge stays as close as possible to the actual expertise, but we are not there yet. The more we can pre-populate that information from other sources, the easier we can make it for people to refine it.
  • Provide the right architecture to support a data-driven organization. We have moved away from the “high-rise” architecture where everything is in a massive ERP system, in favor of a “low-rise” architecture with APIs and add-ins to connect different data sources and third-party apps for specific capabilities.

How are you changing the culture in IT to support a data-driven organization?

As a leadership team, we want IT people to adopt user-centric design. We want them to ask “would I enjoy using this application? How can I help people adopt it?” Historically, technology groups have thought of their remit as deploying technology – i.e., If you deliver a system that runs well at scale, then you’ve done a good job. Our perspective is that our job is not done until we’ve got the right people in the right numbers adopting the new capability. That means a whole new mindset for people and it also means hiring the best talent to role model and reinforce those mindsets.

What advice do you have for CIOs who are driving change?

  • “Lead from the side” by encouraging others to step forward. We’ve developed a digitization leadership group where cross-functional digital leaders learn from each other and share experiences. It is convened by our chief digital officer and members of IT are involved, but it is a business transformation group, not a technology group.
  • Don’t wait. As Arnold Glasgow says, “The trouble with the future is that it usually arrives before we’re ready for it.” Technology leaders tend to like the precision of the ones and zeros, but we all need to get comfortable with rough edges and work-in-progress. For example, we recently upgraded our expenses application to provide better mobile capabilities for processing receipts. But it’s complex because expense rules vary by country and regions. With our focus on improving the employee experience, we wanted to roll out quickly, which meant not waiting to integrate all the existing capabilities (such as a fraud detection tool). Rather than wait, we agreed with our Finance function to build in functionality gradually. That is to say, we reduced the functionality (to start with) in favor of the user experience.
  • Always simplify your architecture. It is hard to get funding for pure technology simplification that doesn’t have a direct business impact. Our approach is to have one eye on simplification while delivering new tools. We’ve identified 190 different legacy data stores and applications that need to be retired. So, we set a target of three years, with the goal of retiring a good percentage of them every year. For example, when we implemented a new staffing application, that was the time to retire five disparate tools related to staffing in one form or another. But our IT leadership team did not decide which to retire; we left those decisions to the relevant product managers who can gauge the business value much better. We just keep the score – i.e., How well are we tracking against the decommission list?
  • Ruthlessly prioritize. Demand will always outstrip your capacity, so it is critical you make sure your teams are working on the most important outcomes. Involving your stakeholders in those tradeoff decisions also helps everyone feel joint accountability for the priorities and respective timelines.
  • Be transparent. For many organizations, IT is a black box, which can lead to a lot of questions about what you are doing and why. You are constantly educating and re-educating your key stakeholders. If you can increase your transparency in terms of backlogs, priorities, OKRs, and financials, then your stakeholders can see that you are minding the store responsibly. That builds trust and collaboration. Most interestingly, this transparency also helps guide teams with day-to-day decisions that advance the goals of the customers, stakeholders, the function, and ultimately, the firm.
  • Take symbolic actions. Four years ago, we renamed IT as the “Technology & Digital” group. Does the actual name really matter? Not really, but it symbolizes that digital does matter. That kind of symbolic action is important to supporting your message of change.

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How Does a SaaS Business Model Work? Types, Stages, & Key Benefits

You’ve got a promising SaaS product. But how do you build the right business model to lift that solution—and your brand—to long-term profitability? From revenue to pricing to measuring performance, this is the ultimate guide to help SaaS CFOs design a winning strategy.

saas business model featured image

A successful SaaS business model supports fast revenue growth, efficient operations, and scale. That’s why so many SaaS leaders subscribe to the philosophy of the “ Rule of 40 ,” which argues that a SaaS company’s growth rate and free cash flow rate should add up to at least 40 percent.

Despite this industry maxim, most SaaS businesses fall very short of this mark. According to McKinsey, the median combined growth rate and free cash flow rate of the top 100 public SaaS companies in the U.S. was only around 32 percent . To push this number higher, tech companies need a SaaS business model that aligns with the brand’s stage of growth, go-to-market strategy, funding runway, and overall business strategy.

Rule of 40 infographic

SaaS Business Model Definition

A software-as-a-service (SaaS) business model is a software delivery service that licenses access to a centralized software product on a subscription basis.

From Netflix to Microsoft Office to countless cloud-based business software solutions, the switch from traditional product-based software purchases to a SaaS business model has brought a number of significant changes to the brand-customer relationship. Even some non-tech businesses have shown an interest in developing new products that allow the company to leverage the core pillars of a SaaS business model.

Recurring Revenue

We’ve come a long way from the days of selling software on a CD. Today’s software is more commonly sold via cloud-based SaaS services which charge a subscription in exchange for access and usage. 

The recurring payments from these subscriptions provide a more consistent stream of revenue to stabilize cash flow and the ability to forecast future earnings.

Heightened Customer Retention

The subscription-based structure of a SaaS business model inherently supports customer retention by requiring an ongoing subscription to license the company’s software. For mission-critical technologies (like CRM ) and consumer products that offer a strong user experience, the potential for continued customer retention and brand loyalty is high.

SaaS business models can further support high customer retention by creating value out of long-term relationships. 

Consistent Updates

Traditional, one-time software purchases meant that software licensees were stuck with a static product. Small security updates may have been available for download but dramatic changes to the software’s capabilities and functionality were nearly impossible to implement.

This limitation doesn’t exist with a SaaS solution. Cloud computing allows the software provider to continually release new updates that keep the software on the cutting edge.

Creating a Moat

An effective SaaS business model will build a formidable moat that insulates the brand against the threat of competition. It’s about more than just the value the SaaS solution offers; this represents the difficulty rival brands will face in trying to recreate this value through services of their own.

The cost of switching away from your business can also support your moat. When customers risk losing efficiencies, data, or other assets and advantages they enjoy with your software, the cost of jumping over to a rival is greater. As your business scales its customer base, consider how new economies of scale can help control expenses and optimize pricing.

If you want to create a business with a nearly inescapable moat, try your hand at creating an ERP system … most companies choose their system once, refusing to change ever again.

Utilizing Customer Feedback

Real-time feedback from existing customers can be directly applied to your software development and UX design processes. Whether launching new features or taking the pulse of the capabilities your customers are clamoring for, this feedback can support more iterative development that accelerates innovation and improves the quality of your overall product.

SaaS Business Stages: A Three-Phase Approach

By the time SaaS businesses become industry leaders and household names, they’ve already slogged through the early growth stages and long-term planning that made their present-day success possible.

Here’s a look at the lifecycle of a typical SaaS business:

Early Stage

In the earliest stages of building a SaaS business, operations are lean, and many employees, from the entrepreneurs that founded it to the newest recruits, may be expected to wear multiple hats.

Products are likely to be still in development, with limited features and few—if any—customers. Early-stage SaaS businesses may be seeking pre-seed funding to accelerate their growth timeline and make strategic hires that will prepare the company to scale its operations.

Growth Stage

Most SaaS businesses enter their growth stage with an infusion of funding to support marketing and other mechanisms designed to scale the software’s user base. Monthly recurring revenue will start to develop, and the company’s growth rate and free cash flow rate should start to tick upward.

The business itself is probably filling out a number of new positions to support its operations at scale. New investment opportunities may also arise as the SaaS offering shows promise and popularity among a select audience. At some point during this growth phase, the company may achieve profitability.

Mature Stage

Once a SaaS business has built a stable customer base driving monthly recurring revenue to support its operations at scale, it has entered the mature stage. This means the company has a core customer base, is retaining customers, and is performing well across other key performance metrics prioritized by the company.

Despite achieving profitability, mature-stage SaaS companies may want to re-evaluate their pricing and revenue models to make sure they fit the company’s goals at this point. 

As customer growth slows, for example, new pricing strategies may offer a path to reviving their revenue growth rate (or disconnecting it from new customer growth altogether).

Types of SaaS Revenue Models

Even before you’ve converted your first customer , every SaaS business needs to identify a revenue model that will guide its approach to revenue generation.

As SaaS companies grow, new revenue models may be necessary. Here’s a look at six of the most common revenue models for SaaS CFOs to consider.

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1. Ad-Based Revenue Model

Ad-based SaaS revenue models generate earnings through ad impressions when the user is active on the website or app. Businesses can sell this ad space either directly to advertisers or through a third-party ad vendor.

This revenue model allows users to access the SaaS solution without paying for a subscription, eliminating a key barrier to entry and increasing the potential for new customer acquisition—although too many ads can degrade the user experience.

  • Best for: SaaS solutions that involve a lot of active user time in the app or platform.
  • Worst for: Early-stage and other SaaS businesses whose small customer base severely limits the revenue generation from ad exposures.

2. Affiliate Revenue Model

Instead of selling ads to generate revenue, an affiliate revenue model offers paid affiliate links that generate revenue in lieu of a paid subscription. Revenue is earned whenever users click on paid links.

While the potential earning from affiliate links can be higher than paid ads, audience relevance can be a big factor in determining this earning potential. And earnings can be uncertain: while ads generate revenue by impressions, affiliate links are dependent upon a user's action.

  • Best for: Niche SaaS solutions that can refer customers to related services and integrations without the risk of losing customers.
  • Worst for: Growth-stage and mature SaaS businesses hoping to deepen customer relationships through bundled services. Plus, as with the ad-based revenue model, early-stage businesses may not have enough customers to generate significant affiliate revenue.

3. Channel Sales

Channel sales is a revenue model that leverages established partners and sells the SaaS solution to their built-in audience. Many SaaS businesses will identify opportunities where an existing tech partner or vendor could promote and sell the SaaS product to their audience in exchange for a sales commission.

This revenue model can be a great way to drive sales without your own in-house sales team, and it can offer a path for early-stage SaaS brands to acquire new customers in spite of limited brand awareness.

  • Best for: SaaS solution providers building products on top of supportive architecture such as VMware, Azure, etc.
  • Worst for: SaaS businesses without clear technology partners or “channel agents” to drive referrals and sales.

4. Direct Sales

Direct selling puts your sales team in charge of customer acquisition, cutting out the commissions charged by channel sales models. In this scenario, your own sales team is directly engaging with new prospects and is responsible for growing your customer base.

The challenge of direct sales is that your growth is limited by the bandwidth and efficacy of your sales team, which can turn direct selling into a drain on resources. But direct selling also offers a more strategic path to qualifying prospects and onboarding promising new customers.

  • Best for: SaaS solutions with a high entry price-point and/or customer lifetime value; particularly B2B SaaS solutions.
  • Worst for: Consumer SaaS solutions with low monthly price-point.

5. Freemium Model

The “freemium” approach offers some version of your SaaS product for free in hopes of earning the trust and appreciation of those customers. Ideally, freemium SaaS models lead to paid conversion opportunities as customers opt for subscriptions that deliver more capabilities and value (think Slack to Slack premium).

Freemium is a great way to get a foot in the door with customers, particularly for B2C SaaS businesses, although a poor user experience can lead to wasted expenses that don’t deliver worthwhile revenue returns.

  • Best for: SaaS solutions that can tier solution performance and capabilities to create upsell opportunities.
  • Worst for: B2B SaaS products catering to a niche audience. 

6. Subscription Revenue Model

One of the most popular SaaS revenue models is the subscription approach, which charges accounts on a regular basis (usually a monthly subscription) for access to the software. While not always feasible for younger SaaS brands without a proven product-market fit, subscription models offer recurring revenue and a relatively clear annual recurring revenue (ARR) figure, which makes it a preferred strategy among CFOs and business owners.

  • Best for: Later-stage growth- and mature-stage SaaS businesses prioritizing recurring revenue and free cash flow.
  • Worst for: Early-stage SaaS businesses focused on building brand awareness and demonstrating the value of its product to customers.

Types of SaaS Pricing Models

Your revenue model determines the mechanisms by which your SaaS business will bring in money. Your pricing strategy, on the other hand, is the process by which you choose how much to charge your customers, and how that pricing will be charged to those users.

Here’s a look at the most widely used SaaS pricing models:

Flat-Rate Pricing

It’s a simple transaction: customers are billed a flat rate for access to your SaaS solution. The selling and accounting is easy this way: unlike other pricing models that can involve complex calculations, a flat-rate approach is easy to record.

At the same time, flat-rate prices are an all-or-nothing approach, which may not offer the most optimized approach to revenue generation. This pricing model can also be inefficient in cases where SaaS customers can vary widely in their usage and resource requirements.

Consumption-Based Pricing (AKA Usage-Based Pricing)

Consumption-based pricing can be highly scalable based on how much each customer uses your SaaS solution. This ensures that the price is always aligned with the value it offers your users. It also makes it easier for customers to test-drive your solution before choosing their level of investment.

The drawback of usage-based pricing is that, as usage fluctuates, so does your company’s revenue, which can impact financial forecasting and free cash flow. Variance in pricing can also frustrate customers billed for high-usage periods, putting them at risk of seeking out a more stable alternative.

More and more SaaS businesses are turning toward usage-based pricing models over the last few years, which indicates where consumer demand is headed.

Tiered Pricing (Model)

Tiered pricing is one of the most common SaaS models thanks to its flexible pricing options and recurrent revenue generation. With tiered pricing, SaaS businesses offer a select number of pricing options that are targeted to specific buyer personas and use cases.

These tiers make it easier for customers to find a price level that fits their needs and budget, and it creates a natural upsell opportunity. But managing these tiers can also mean more work for the business, and broad-tiered options could pull internal resources away from focusing on your core offerings and audience.

Per-User Pricing

B2B SaaS solutions may be interested in adopting per-user pricing, which charges accounts upfront, then recurring, based on the number of users accessing the platform. This is a common pricing model used by businesses where multiple employees will be regularly using the SaaS solution, with examples ranging from project management tools to e-commerce platforms.

Per-user pricing is simple, easy to adjust over time, and scales along with the customer’s use. But it’s inevitable that some customers will try to cheat the system, and governance of these accounts is another expense cutting into your profits.

Netflix and Costco have both made headlines for their crackdowns on membership sharing.

Per-Active-User Pricing

One risk of per-user pricing is that customers could end up paying for users that aren’t active on the platform. To guard against this, some SaaS businesses—including Asana and Salesforce , among others—charge only for active user accounts. This lets customers create as many user accounts as they want with the assurance that only active users will be billed.

Per-Feature Pricing

Although similar in design to the tiered pricing model, per-feature pricing sets different price levels based on the features and capabilities at each level of investment. The value proposition is clear to customers: if you want better performance from the platform, you can upgrade to a higher tier and unlock new benefits.

A per-feature approach can lay a foundation for upselling, and it offers transparency when customers want to know what they’re getting for their investment. Choosing how to separate features across different tiers can be complicated, though, as you don’t want to turn your entire company into an a la carte menu.

Freemium Pricing

Freemium pricing can look a lot like a tiered or per-feature model, with the exception that one tier offers basic access to the SaaS solution, free of charge.

As with a freemium revenue model, there are benefits to this approach—particularly when trying to onboard a broad customer base that can create upsell opportunities. But giving away part of your SaaS solution experience can be risky, and you might miss out on a lot of revenue that could have been generated by making your entry-level tier inexpensive, rather than free. Generally speaking, this model is favored by companies that have a lot of close substitutes and alternatives. If your market isn’t yet saturated and your product is easy to understand, I wouldn’t recommend this.

SaaS Distribution Models

Your distribution strategy dictates the channels through which your SaaS solution will reach your customers. Distribution can take two forms: direct distribution between the SaaS business and its customers, and indirect distribution facilitated by a third party.

Although some businesses—such as Amazon—use direct and indirect distribution alongside one another, many SaaS solutions are reliant on just one approach. 

Direct Distribution

With direct distribution, SaaS solutions are delivered directly via a sales team or are accessed through an online self-service portal, such as a website. Direct distribution may also enlist the help of consultants and account managers to help onboard new software solutions for each customer.

Direct distribution is beneficial because it lets you control the full supply chain and maximize the value of each new customer acquisition. SaaS sales teams can operate with greater independence through this model. However, the lack of a third party can hinder your reach and customer acquisition opportunities, making it difficult to scale your company with limited resources.

Indirect Distribution

App stores, white-label resellers, and professional services firms are examples of indirect distribution that leverage an existing channel to reach new users with your SaaS solution. These indirect channels are often prized for their ability to quickly engage a large, relevant audience.

This reach comes at a price, though: some resellers will want a commission for their referrals, while app stores and marketplaces will come with additional requirements, fees, and dependencies that can impact the speed and quality of your delivery. These third parties may also handle customer service issues on your behalf, which can reduce your workload but also limit your ability to control the customer service experience (and receive direct feedback). 

The 5 Biggest Benefits of the SaaS Business Model

The most significant benefits of adopting a SaaS business model will depend on your company’s growth stage, your industry, and the composition of your customer base. 

Regardless of your company’s individual priorities, though, SaaS business models have inspired copycat modeling among non-tech businesses because of the distinct benefits this approach can offer. Here are five of the biggest advantages businesses are targeting when they develop a SaaS business model.

Build Once, Sell Twice

Software products are sold once. Software-as-a-service, though, is continuously sold through its subscription model. 

This ongoing relationship allows software to essentially be re-sold not just once or twice, but many times over the lifespan of each customer relationship—as long as the software continues delivering value for its users.

Income Predictability

After the initial investment to develop a SaaS infrastructure, subscription-based customer acquisition offers a fast path to revenue generation and free cash flow at scale. 

Incoming revenues are more predictable, which supports financial forecasting and re-investment into initiatives aimed at continuing to scale the business.

Speed of Innovation

Customer feedback influencing iterative development cycles is easily supported by a SaaS approach. These inputs, combined with recurring revenue, allow SaaS businesses to be more agile and responsive to market changes—even when that market change requires the business to change its core offerings.

Sometimes this means developing new products to meet a market need. Other times, it may mean simplifying SaaS services to improve the customer experience—which motivated Shopify to sell its logistics business and focus on the core offerings that mattered most to its business model and customer base.

Anywhere, Anytime

SaaS businesses aren’t limited by geography, time, or product availability. A SaaS solution can be accessed anytime, from anywhere—and, in many cases, regardless of the scale of your SaaS needs.

Minimum Viable Product

Since software offerings can be iterated and optimized over time, SaaS brands don’t have to hold the release of their product until it’s been perfected. A SaaS business can (and should) start small with a minimum viable product release that can start generating revenue, user feedback, and brand visibility.

Once this minimum viable product is launched, additional capabilities and products can be considered as strategies for enriching the brand’s value to its customers.

Disadvantages of the SaaS Business Model

For most software-as-a-service businesses, the benefits of a SaaS business model far outweigh the possible disadvantages of this approach. Still, certain limitations could present problems for certain companies, and CFOs must know how to recognize and adapt to these challenges.

Here are the most common disadvantages brought on by a SaaS business model.

Large Capital Requirements

Recent access to AI coding tools may help lower the cost of SaaS product development, but the total investment to build a SaaS company remains significant—especially if you want to develop a solution that can’t be quickly replicated by your competition.

Funding and investor support are essential to launching a SaaS product and laying a foundation for revenue growth. These capital requirements can make a SaaS business model untenable for a small startup brand eager to bootstrap its way to success.

Security is Your Responsibility

SaaS companies are in the business of handling their users’ data. Before you convert your first customer, your business needs a comprehensive security strategy that mitigates the risk of network breaches and data loss. Depending on your industry, this security infrastructure may also be subject to compliance requirements.

Remember: it only takes one security breach to frustrate customers, tarnish your brand’s reputation, and undo all of the hard work you’ve done to build your company on a strong financial foundation. 

Your Offering May Be Easily Replicated

For all of the cost and complexity of building a SaaS business, new SaaS operations must be mindful of how easily a deep-pocketed competitor could build and launch a comparable product that cuts into your potential market share.

A good SaaS business model not only considers the value offered to its customers but also the likelihood that another company could copy this offering. Greater complexity can make your product harder to replicate, but this may further increase your capital requirements.

High Competition & Low Customer Loyalty

It’s the biggest downside of having a low barrier to entry: even if your offering can’t be perfectly replicated by a competitor, you still have to worry about alternative solutions crowding your market and attempting to undercut your pricing, beat your solution on performance, upstage the value of your product through bundled services, or all of the above.

The accelerated time-to-launch is a great benefit of building a SaaS business, but it also means the market can evolve quickly—and early industry leaders can quickly get swallowed up by the competition.

No/Low Early Profitability

Most SaaS businesses don’t achieve profitability until they’re well into their growth phase. Even as revenue starts, those funds must be reinvested into growth strategies to help achieve the growth required for long-term profitability and sustainability.

It’s an investment in the future: profits take longer to achieve, but the overall profit potential is greater. In the short term, however, this means early-stage SaaS CFOs are going to see business expenses far exceed revenues.

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Performance metrics will tell the real story of whether your SaaS business model is delivering results. But different metrics can offer a different perspective on your company’s success.

To paint the full picture, pay close attention to the following data points.

Churn reflects your company’s customer attrition. The more active customers your SaaS business loses over a certain period of time, the more difficult it will be to sustain MRR and growth.

Churn is different from your total customer growth because it reflects how often active customers are leaving your solution. While ideal churn rates can vary, a healthy B2C SaaS company will have a churn rate between two and eight percent. For B2B SaaS brands, the ideal monthly churn should be under five percent . 

Customer Lifetime Value (LTV)

Your customer lifetime value reflects the average revenue each new customer relationship will generate. LTV is an important metric when funding marketing and sales efforts and calculating ROI. 

The aggressive advertising investments by Starbucks are a great example. While the cost of a cup of coffee is relatively cheap, Starbucks has calculated its average customer LTV to be greater than $14,000 . As a result, the company can still turn a massive long-term profit even if it spends hundreds of dollars trying to convert a single customer. LTV can also help you determine whether your SaaS solution is doing enough to generate long-term revenue from your customer relationships. 

Customer Acquisition Cost (CAC)

Customer acquisition cost is the amount of money required to acquire a new customer. This encompasses all of your acquisition expenses, including marketing, advertising, sales, promotional offers, and other related costs. 

A lower CAC equates to faster growth potential within your fixed advertising and marketing budgets. CAC must also be considered alongside LTV , though: the lower CAC is in relation to LTV, the better your long-term profit potential.

CAC Payback Period

This metric refers to the amount of time it takes for a customer’s revenue generation to exceed their acquisition cost . 

While this payback period can vary depending on the type of SaaS solution, the industry, and your company’s stage of growth, a general rule of thumb is to aim for a payback period of 12 months or less. High-performing SaaS businesses may complete this payback in as little as five to seven months.

Customer Engagement Score

CES is a measurement of how engaged customers are with your SaaS solution. This calculation can be more subjective, and the methods of scoring may vary depending on what your want to prioritize in your SaaS experience, but typical customer engagement score metrics will include the frequency of accessing and using the product, the time spent on your SaaS platform, upgrades and renewals, referral rates, and frequency of customer support tickets.

Align Your SaaS Business Model With Your Brand’s Immediate Goals

SaaS business models are never set in stone. Instead, the pricing, revenue, distribution, and other facets involved should all be chosen with a focus on reaching your company’s next stage of growth.

As SaaS brands scale and evolve, changes to this business model may be necessary. As you approach these tough decisions, it’s helpful to talk with other CFOs who have been through these growth cycles and can help you balance your company’s short-term revenue needs with your long-term growth goals.

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False friends or good ends? The CIO’s four-point guide to navigating technology trends

“Did you see the article about blockchain on the paper’s home page? I think we need blockchain, too.” “We should give all our IT to an offshore system integrator—that will save a lot of money. Our competitors are doing the same thing.” “We need to do something about generative AI right away!”

Many who work in IT have heard variations of these statements from well-meaning senior colleagues. And given how much technology underpins so many trends, as well as the increasing pace of innovation, IT leaders can expect to hear more of them and feel pressure to act on them.

Sometimes it makes a lot of sense to act quickly on a trend. Innovation, after all, is a hallmark of successful companies. But not all trends are created equal. The annals of many IT organizations are littered with bold initiatives in trends that created a lot of excitement but not much value. Moving quickly to chase a trend often bogs an organization down, leads to wasted spend, and takes attention away from important priorities.

For this reason, the ability to evaluate trends quickly and communicate their relevance to the business is becoming a critical capability for the modern CIO. In practice, it is rarely as simple as saying “yes” or “no” to investment in a particular trend. Trends are unpredictable, change with time, and their relevance to a given business often waxes or wanes. Instead, CIOs need a clear set of parameters to rely on both for evaluating trends and for determining which posture to take for engagement with them: first mover, fast follower, slow adopter, or sometimes non-partaker.

The four guides for determining a trend’s relevance

We researched trends of the past to find patterns that can help us better understand how to evaluate them in terms of their relevance to a business. There are many reasons why attempts to turn a promising trend into a profitable one for any given business may fail—insufficient talent or leadership nonalignment come to mind. But we have also found that trends that add value have inherent attributes that make them particularly valuable to any business. We’ve boiled them down to the following four:

  • Disruptive business value: The trend can result in measurable value to the business.
  • Independence: The trend allows the organization to work in smaller, more independent units.
  • Connectivity: The trend reduces friction in the organization’s connectivity.
  • Extensibility: The trend can broadly shape and improve the organization’s technology and management practices.

You don’t necessarily need a green light across each of these four parameters to make investment in a trend worthwhile. But if one of them comes up red or yellow, it’s worth taking a closer look before making a significant commitment. And while trends often initially aim to address just one of these areas, their relevance and impact rise dramatically when they can be applied coherently to all four.

It’s worth emphasizing that this evaluation isn’t a simple checklist. It requires rigor in the analysis, a willingness to review the analysis on its merits (without being influenced by how it might serve a narrow but favored “pet” project”), and creativity—some trends aren’t particularly meaningful on their own, but in combination (virtualization and cloud, for example) can have greater potential.

1. Disruptive business value

Almost any trend or development has the potential to improve something in an organization. The question is whether that improvement is worth what it costs. It’s important to understand the trade-offs. You may save money or generate value in one area by adopting a certain trend, but will it cost you in another?

The most important points to determine are whether the value is to IT alone or to the business overall, whether that value is merely incremental or significant, and whether success is clearly measurable in KPIs. If a trend improves an IT process but can’t be directly linked to a business advantage, then it’s probably not worth a significant investment. For example, much of the benefit of cloud computing comes not from improvements to IT productivity but from how it accelerates and enables business processes and innovation.

The value of some trends will depend on the sector where they are applied. Blockchain’s value potential, for example, has differed from industry to industry. While in some areas of financial services, such as cryptocurrency and collateral management, blockchain has the potential to create a lot of value, in other industries, such as consumer packaged goods, the value potential is less clear.

Key questions

  • Does this trend provide disruptive business value? If the value is incremental or isolated to some operational improvement in IT, then the trend isn’t really worth a “big bet.”
  • How will you measure value capture? Every initiative has metrics, but they are often hazy or do not clearly reflect business value. Be disciplined in developing measurable objectives and key results (OKRs), and determine which KPIs contribute to them. This clarity is critical during implementation to see whether what you’re working on is delivering value and why or why not.

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2. independence.

One of the tech executive’s key challenges is that IT often has too many interdependencies, which leads to technical debt and administrative processes such as alignment meetings and process coordination—for example, when changes to the billing system depend on numerous other systems and development teams, meetings and delays are inevitable consequences.

The concept of “modularity” has been in vogue for almost two decades now, but the enthusiasm for it has generally not been matched in its implementation. APIs have certainly helped, but they don’t address the important organizational changes that also need to happen to reduce dependencies. That’s where moving toward a product and platform operating model —where independent teams work on user-facing products while platform teams build capabilities to support them—can have significant impact. Assessing how a trend can be profitably adopted and supported by either product or platform teams should be a critical criterion for evaluating its potential.

Many of us are familiar with the big trend some 10 to 15 years ago toward large-scale outsourcing of IT to an external system provider. The rationale was that external providers would reduce IT’s overall cost. For some industries with low margins, large-scale outsourcing deals were at least partially successful. But the system dependencies didn’t change. So, as the need for speed and flexibility in technology grew, the savings from outsourcing were increasingly outweighed by the system dependencies that remained in place and slowed the pace of development. With modern software as a service (SaaS), on the other hand, only a specific, relatively independent, and clearly contained functionality is outsourced to a vendor, making this approach much more scalable.

  • Does this trend allow me to make my teams more independent—for example, by automating communication at interfaces or reducing the need for coordination and up-front planning?
  • To what degree will this trend enable a more modular IT estate? Look for specific benefits, like a trend’s ability to separate different applications from each other or abstract layers of the technology stack.
  • How many parts of the IT estate are needed to make this trend run well? The greater the number, the greater the complexity and the more likely you’ll run into inevitable workarounds that will add to technical debt.

3. Connectivity

While independence is important, a trend that operates like a satellite on its own or divides the organization up into disconnected units isn’t going to lead to at-scale impact. There is a difference between dependency, which isn’t good, and leverage, which is critical for delivering value.

That difference was clearly illustrated in enterprise service buses (ESBs), which afforded independence but required additional alignment and orchestration, sometimes through a single central team, which created a bottleneck.

Virtualization is another trend that highlights the need to balance independence and connectivity. Initially focused on improving the usage of hardware assets—specifically, the CPU—virtualization also made applications less dependent on each other and on larger systems by not forcing everything to run on a single server. But it provided limited connectivity between individual virtual machines. There was no structured capability in place that made it easy and convenient to move workloads, scale them, and manage the connections. This changed with cloud computing and containerization , which connected individual machines through a central management layer.

In contrast, modern microservices patterns aim to both improve independence and clarify the interfaces and thus improve connectivity by reducing the need for communication or a central coordination mechanism.

“Improved connectivity” should not be misunderstood as more communications—that’s a recipe for creating more dependencies. Improved connectivity is often reached through more clarity on the interfaces, reducing the need for communication.

  • Does this trend increase clarity at the interfaces and reduce the need for coordination? You’re looking for a trend that can use stable and reusable interfaces between technologies.
  • Does this trend lead teams to work with each other more effectively due to less “waste” in communications?
  • In what way can this trend leverage existing technology assets? It will be important to understand what kinds of interfaces will make the necessary connections, and how easily they can be implemented and maintained.

The CIO Agenda

The CIO Agenda

4. extensibility.

The impact of a technology trend increases with its applicability and coherence across the IT estate. A technology trend that touches only one part of the IT estate in isolation or is managed simply as a “tech product” does not often have the widespread impact that comes with true innovation. Impact often requires companies to think through both the technology and operational implications to open up the potential. Broad applicability is where you get to scale.

Virtualization, microservices, or SaaS-based services, for example, were less successful when they were managed as a pure tech product. Only when combined with enabling factors on the operating side, such as agile, DevOps, and the necessary support structures (such as budgeting roles and HR support) did they have much greater impact.

Similarly, agile works best when all relevant parts of the company work in agile ways. (The impact of agile developer teams is improved when operations, for example, also work in agile ways, which is how we came to DevOps.) The key question for the CIO, then, is how to adjust the technology estate to extend the range of application across technology and the business.

  • How can IT management practices adapt or innovate with the trend?
  • Will this trend require the business operations and decision processes to change in order to develop its full potential?
  • Are all the support processes (such as budgeting, HR, architecture) in place to support the trend?

Adopt or not: A strategic decision

As they say in comedy, timing is everything, and that’s just as true when it comes to trends. Going in on a trend too early or too late can sometimes be worse than doing nothing at all. Just as important as evaluating a trend’s “bona fides” according to the four parameters described above is determining how best to engage with it. CIOs should consider four possible engagement approaches:

  • First mover: This engagement makes the most sense in the case where the trend has significant impact on the company’s core business model (which is to say, it’s a matter of business survival). This approach generally involves investing significant resources of time, people, and money. The big trap here is convincing yourself that the first-mover approach is the only viable option.
  • Fast follower: This approach is best applied when the trend could have an important impact on your business model or open up a significant revenue stream. This engagement posture can work when the trend is still too early in its maturity cycle to understand how it can best be harnessed, or when the business doesn’t yet have sufficient capabilities in place to act on the trend. A good signal of a trend’s importance is when big players lead the innovation and go all in. The danger here is taking a “wait and see” approach too long and finding yourself much further behind your competitors than you expected. Greenlighting pilots can make it seem that you’re taking action, but unless those pilots are closely tracked and—most importantly—scaled, then this activity has no real impact.
  • Slow adopter: This approach is an acceptable option when the trend isn’t directly relevant to the core business or is not mature. It might make sense for niche applications of a trend. The danger here is that complacency and an overly narrow view of the trend’s relevance, such as focusing only on how existing competitors might use it and failing to consider emerging players, leave your company too far behind to catch up.
  • Non-partaker: Some trends just don’t make sense for a business to adopt. This is often an unpopular approach when the board or senior management is demanding action. A clear view of business goals and the impact of a trend on those goals is critical. But complacency is also a danger here when legacy-driven thinking argues that a given trend “doesn’t apply to us.”

The call on whether and how to adopt a trend is not a one-time decision. It requires continual review as technology matures and evolves, new implementation models and supporting services scale, or the market situation shifts. But CIOs who use the four parameters as a compass to determine relevance and think through their engagement options can better guide their organizations toward turning trends into value.

Oliver Bossert is a partner in McKinsey’s Frankfurt office, where Gérard Richter is a senior partner; and Klaas Ole Kürtz is a senior practice manager for McKinsey Technology, based in the Hamburg office.

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How Do SaaS Startups Make Money? | SaaS Revenue Model

Rishabh Rathi

Rishabh Rathi , Anga Mahatara

Software as a Service (or SaaS) is a new method for delivering software applications over the internet. It does not require any installation or maintenance of the software to avail of the services. The software is hosted by a third party and one can access it by paying a subscription fee.

The benefits of the SaaS model are clear. It provides lower costs, lower commitment risk, and a try-before-you-buy model, which gives customers a remarkable opportunity to assess a product before making a purchase. Indeed, the benefit is so clear that a 2017 study conducted by BetterCloud found that 86% of organizations estimate that 80% of their business apps will be delivered through the SaaS model by 2022.

Growth chart of SaaS business apps in companies

In 2022, the SaaS market valuation is at $186.6 billion and has an annual growth rate of around 18%. It is projected to grow to $700 billion by 2030.

For software businesses, on the other hand, the SaaS model presented an entirely new way to build, distribute, market, sell, and support a software product. It affects every single part of a software operation. But the most significant change that the SaaS model brought — the one at the root of all the other changes — was the SaaS revenue model. The Software as a Service (SaaS) revenue model is associated with regular, ongoing payments over a defined period, in exchange for using a software application or other tool.

About SaaS SaaS Revenue Model & Its Phases Phase 1: The Initial Sale Phase 2: Retention Revenue Phase 3: Expansion Revenue How to build a great SaaS revenue operation

Software As A Service

SaaS is referred to as a software distribution model in which a cloud provider hosts applications and makes them available to end-users over the internet. In this model, an independent software vendor may contact a third-party cloud provider to host the application.

SaaS is one of the categories of cloud computing that include infrastructure as a service (IaaS), and platform as a service (PaaS). SaaS applications are mostly used by IT professionals, business users, and personal users. Products ranging from entertainment services, like Netflix , to advanced IT tools come under SaaS . SaaS products are mostly marketed to B2B and B2C customers.

As per recent McKinsey & Company study, technology industry analysts have predicted further growth in the SaaS market, and expect to see the market for SaaS products close to $200 billion by the year 2024.

SaaS Revenue Model & Its Phases

Before SaaS, the software revenue model was transactional and all that mattered was the initial sale of the software product. Big, fancy salesmen sold long-term deals for one, two, or even five million dollars a pop. Done. Hands dusted, gong rung, contract signed — all the revenue that was going to come from that deal had been generated. Enter the SaaS revenue model . It swapped the single point of revenue with three essential phases: Initial sale → Retention → Expansion

SaaS Revenue Model

There are three phases of the SaaS Revenue Model as listed below.

  • Phase 1: The Initial Sale
  • Phase 2: Retention Revenue
  • Phase 3: Expansion Revenue

It still exists! And it’s still an essential part of the SaaS revenue model . “Closing” an initial sale includes everything from a simple self-serve upgrade to an annual contract shepherded by an inside salesperson.

If you play this phase well and show strong initial sales growth, you’ll get somewhere with your SaaS business . You’ll probably be able to raise some money, maybe even have a mini-brand — excellent! But these days, an initial sale brings in far less revenue than in the traditional SaaS revenue model. It’s still extremely important — you need a flow of new customers — but you also need to move on too.

saas business model mckinsey

“You mean we have to keep them happy? Forever??” – Early SaaS pioneer

Quite so, Mr. Early SaaS Pioneer. There’s a new (SaaS) revenue model in town. Most early players, however, maintain the sales-first mentality even though they’re selling much smaller, month-to-month deals. They’re celebrating the initial sale disproportionately which is not correct for SaaS.

On the other hand, some SaaS companies quickly realized the importance of retention. Indeed, they saw that an initial sale didn’t matter much if a new account was canceled three, six — even 12 months later. They realized they couldn’t sustain growth if they churned the customers they brought in. These people know how to play the game of SaaS.

Today’s SaaS pros realize that retention is the biggest revenue opportunity in SaaS. An initial sale might get you $500 in the bank when you convert that deal. But retention, retention will bring in that amount times the number of months the account stays active. And why? Here’s some fast math on that point:

  • 1 month (initial sale): $500
  • x 12 months = $6k
  • x 24 months = $12k
  • x 36 months = $24k

Indeed, the revenue opportunity from retention is exponentially larger than the initial sale. Execute well in this second phase, my friend, and you will build a solid, sustainable SaaS business. Excellent! But wait — if you want to build a great SaaS business, crush the competition, and have a shot at an IPO , you’ll have to master the third phase of the SaaS revenue model : Expansion.

Often overlooked, always important — this is where the true secret to SaaS growth lies. Savvy SaaS teams quickly realized that they could drive revenue growth by expanding existing accounts. Upsells, cross-sells, and any other sales that could generate additional revenue from existing customers became SaaS staples. And it worked earlier, mainly because the opportunity for second-order revenue was huge.

Calculating expansion revenue growth rate

You understand the realities of the three phases of SaaS revenue. Excellent! But that’s only half the battle. The other half is executing against it. You’ll need to shift the way you look at adoption, customer service, sales, and marketing. Thanks to the SaaS model, the operations of software businesses are changing.

Customer relationships: In the SaaS revenue model, customer relationships are based on the ongoing delivery of customer value.

Marketing issues related to the SaaS/subscription model: Marketing strategies focus on growing subscribers through lead generation, branding, goodwill activities, and other efforts to create interest in the product or service.

Operational implications of the SaaS/subscription revenue model: Companies employing the SaaS/subscription revenue model should focus primarily on delivering cost-effective customer value.

Financial and strategic implications: In most cases, successful SaaS/subscription companies build up their subscriber base over a long period. In the interim, they require financing to develop delivery capacity as well as to support efforts to increase the user base.

Key metrics: SaaS/subscription companies consider key metrics to be customer retention and net new growth in subscriber numbers.

Modalities: While SaaS/subscriptions are most commonly thought of as single sales to individual subscribers, the SaaS/ subscription model also works with bulk sales. Rather than selling one subscriber one subscription, a company can sell subscriptions in larger increments for a reduced per-user rate.

Costs and benefits of the SaaS/subscription model: The SaaS/subscription revenue model usually works best when a company is servicing ongoing and continuous customer needs. This means that customer relationships may span several years. It is often challenging to convince new customers to commit to long-term contracts, especially in the case of companies offering novel products or services.

saas business model mckinsey

How to build a great SaaS revenue operation

To build a great SaaS revenue operation, there are three truths teams must accept:

  • SaaS revenue goes well beyond an initial sale. There are three essential phases of revenue and a SaaS business must execute well in all three phases to become great.
  • Building a management structure that provides continuity and strategic consistency across these three phases of revenue will ensure the best shot at success.
  • Product engagement is the key to winning the game of SaaS. Great SaaS operations understand this and find a way to bring this data to their team in the most actionable way possible. Great SaaS revenue models seamlessly integrate product engagement insights into every part of their customer-facing operations.

A good SaaS model provides lower costs, and lower commitment risk, and a try-before-you-buy model gives customers a remarkable opportunity to assess a product before making a purchase. For software businesses, on the other hand, the SaaS model presents an entirely new way to build, distribute, market, sell, and support a software product.

Now that you know about the revenue model of SaaS, let's get on board and start executing them in your business.

What is SaaS?

Software as a service (or SaaS) is a way of delivering applications over the Internet - as a service. Instead of installing and maintaining software, you simply access it via the Internet, freeing yourself from complex software and hardware management.

What are the examples of SaaS?

Examples of SaaS are - BigCommerce, Google Apps, Salesforce, Dropbox, MailChimp, ZenDesk, DocuSign, Slack, and Hubspot. PaaS Examples: AWS Elastic Beanstalk, Heroku, Windows Azure (mostly used as PaaS), Force.com, OpenShift, Apache Stratos, Magento Commerce Cloud.

What are the three phases of the SaaS Revenue Model?

The three phases of the SaaS Revenue Model are:-

Is Netflix a SaaS?

Yes, Netflix is a SaaS that offers software to watch licensed videos. It follows a subscription-based model wherein the user can choose the suitable one as per its requirement.

Is Facebook a SaaS?

SaaS simply stands for "Software as a Service". Facebook is a consumer network product, not technically SaaS , but there's no other product that provides as many services as Facebook does.

Are mobile apps SaaS?

The new frontier for enterprise software as a service (SaaS) providers appears to be in mobile apps. While desktop platforms are still the backbone of any SaaS product, mobile apps are becoming increasingly important. Mobile apps and API connections are expected to add 0.71% growth to the SaaS Market Size.

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McKinsey & Company is a global management consulting firm that serves leading businesses, governments, non-governmental organizations, and not-for-profits. They help our clients make lasting improvements to their performance and realize their most important goals. Over nearly a century, they’ve built a firm uniquely equipped to this task.

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Cross-selling is a business strategy in which additional services or goods are offered to the primary offering to attract new consumers and retain existing ones. Numerous businesses are increasingly diversifying their product lines with items that have little resemblance to their primary offerings. Walmart is one such example; they used to offer everything but food. They want their stores to function as one-stop shops. Thus, companies mitigate their reliance on particular items and increase overall sustainability by providing other goods and services.

Culture is brand:

It requires workers to live brand values to solve issues, make internal choices, and provide a branded consumer. Developing a distinctive and enduring cultural brand is the advertising industry's holy grail. Utilizing the hazy combination of time, attitude, and emotion to identify and replicate an ideology is near to marketing magic.

Archetypes of business model design:

The business model archetypes include many business personalities and more than one business model linked to various goods or services. There is a common foundation behind the scenes of each unit, but from a management standpoint, each group may operate independently.

Benchmarking services:

Benchmarking is a technique for evaluating performance and gaining insights via data analytics. It may be used to conduct internal research on your firm or compare it to other businesses to enhance business processes and performance indicators following best practices. Typically, three dimensions are measured: quality, time, and cost. In this manner, they may ascertain the targets' performance and, more significantly, the business processes that contribute to these companies' success. The digital transformation era has spawned a slew of data analysis-focused software businesses.


Simplifying many product kinds inside a product group or set of goods. A technique for doing business analysis in which a complex business process is dissected to reveal its constituent parts. Functional decomposition is a technique that may be used to contribute to an understanding and management of large and complicated processes and assist in issue solving. Additionally, functional decomposition is utilized in computer engineering to aid in the creation of software.

Best in class services:

When a firm brings a product to market, it must first create a compelling product and then field a workforce capable of manufacturing it at a competitive price. Neither task is simple to perform effectively; much managerial effort and scholarly study have been dedicated to these issues. Nevertheless, providing a service involves another aspect: managing clients, who are consumers of the service and may also contribute to its creation.

Multiple products or services have been bundled together to enhance the value. Bundling is a marketing technique in which goods or services are bundled to be sold as a single entity. Bundling enables the purchasing of several goods and services from a single vendor. While the goods and services are often linked, they may also consist of different items that appeal to a particular market segment.

Digital transformation:

Digitalization is the systematic and accelerated transformation of company operations, processes, skills, and models to fully exploit the changes and possibilities brought about by digital technology and its effect on society. Digital transformation is a journey with many interconnected intermediate objectives, with the ultimate aim of continuous enhancement of processes, divisions, and the business ecosystem in a hyperconnected age. Therefore, establishing the appropriate bridges for the trip is critical to success.

Consumerization of work:

Consumerization of IT (consumerization) is a term that refers to the process by which Information Technology (IT) begins in the consumer market and then spreads to business and government organizations, primarily as a result of employees utilizing popular consumer market technologies and methods at home and afterward bringing them in the workplace.

Corporate innovation:

Innovation is the outcome of collaborative creativity in turning an idea into a feasible concept, accompanied by a collaborative effort to bring that concept to life as a product, service, or process improvement. The digital era has created an environment conducive to business model innovation since technology has transformed how businesses operate and provide services to consumers.

Codifying a distinctive service capability:

Since their inception, information technology systems have aided in automating corporate operations, increasing productivity, and maximizing efficiency. Now, businesses can take their perfected processes, standardize them, and sell them to other parties. In today's corporate environment, innovation is critical for survival.

Data as a Service (DaaS):

Data as a Service (DaaS) is a relative of Software as a Service in computing (SaaS). As with other members of the as a service (aaS) family, DaaS is based on the idea that the product (in this instance, data) may be delivered to the user on-demand independent of the provider's geographic or organizational isolation from the customer. Additionally, with the advent[when?] of service-oriented architecture (SOA), the platform on which the data sits has become unimportant. This progression paved the way for the relatively recent new idea of DaaS to arise.


Orchestrators are businesses that outsource a substantial portion of their operations and processes to third-party service providers or third-party vendors. The fundamental objective of this business strategy is to concentrate internal resources on core and essential functions while contracting out the remainder of the work to other businesses, thus reducing costs.

Reverse auction:

A reverse auction is a kind of auction in which the bidder and seller take on the roles of each other. In a conventional auction (also referred to as a forward auction), bidders compete for products or services by submitting rising bids. In a reverse auction, vendors fight for the buyer's business, and prices usually fall as sellers underbid one another. A reverse auction is comparable to a unique bid auction. The fundamental concept is the same; nevertheless, a bid auction adheres more closely to the conventional auction structure. For example, each offer is kept private, and only one clear winner is determined after the auction concludes.

Market research:

Market research is any systematic attempt to collect data about target markets or consumers. It is a critical aspect of corporate strategy. While the terms marketing research and market research are frequently used interchangeably, experienced practitioners may want to distinguish between the two, noting that marketing research is concerned with marketing processes. In contrast, market research is concerned with markets. Market research is a critical component of sustaining a competitive edge over rivals.

Software as a Service (SaaS):

Software as a Service (SaaS) is a paradigm for licensing and delivering subscription-based and centrally hosted software. Occasionally, the term on-demand software is used. SaaS is usually accessible through a web browser via a thin client. SaaS has established itself as the de facto delivery mechanism for a large number of commercial apps. SaaS has been integrated into virtually every major enterprise Software company's strategy.

Disruptive trends:

A disruptive technology supplants an existing technology and fundamentally alters an industry or a game-changing innovation that establishes an altogether new industry. Disruptive innovation is defined as an invention that shows a new market and value network and ultimately disrupts an established market and value network, replacing incumbent market-leading companies, products, and alliances.

Knowledge and time:

It performs qualitative and quantitative analysis to determine the effectiveness of management choices in the public and private sectors. Widely regarded as the world's most renowned management consulting firm. Descriptive knowledge, also called declarative knowledge or propositional knowledge, is a subset of information represented in declarative sentences or indicative propositions by definition. This differentiates specific knowledge from what is usually referred to as know-how or procedural knowledge, as well as knowledge of or acquaintance knowledge.

Solution provider:

A solution provider consolidates all goods and services in a particular domain into a single point of contact. As a result, the client is supplied with a unique know-how to improve efficiency and performance. As a Solution Provider, a business may avoid revenue loss by broadening the scope of the service it offers, which adds value to the product. Additionally, close client interaction enables a better understanding of the customer's habits and requirements, enhancing goods and services.

Historically, developing a standard touch sales model for business sales required recruiting and training a Salesforce user who was tasked with the responsibility of generating quality leads, arranging face-to-face meetings, giving presentations, and eventually closing transactions. However, the idea of a low-touch sales strategy is not new; it dates all the way back to the 1980s.

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Maximize revenue with these 3 foundational building blocks.

saas business model mckinsey

Every CEO strives to maximize revenue, but at some point, they face the difficult challenge of missing a revenue target. The target may be self-imposed or approved by a board, but in either case, one thing is clear: your current revenue engine isn’t delivering the growth you expect and something needs to change.

When setting revenue targets the key metric to consider is revenue growth. By looking at historical growth rates, you can more accurately forecast next year's numbers. Revenue growth is a top driver for exit valuation because investors, executives, and equity holders all want their equity value to increase. Additionally, revenue growth increases free cash flow that can be reinvested in the business, creating a virtuous cycle for growing a company.

Whether you are grooming your company for a life-changing exit, trying to maximize revenue, or grow your free cash flow, the underlying reasons for underperforming against revenue targets are often the same.

The top 3 reasons for missing revenue targets

You may expect the top reason for missing your revenue targets to be an underperforming sales team, but unfortunately, the problem usually isn’t that simple. After helping many companies overcome slow-growth issues, I’ve found that the underlying problems most SaaS businesses face are almost universal:

1. You are selling the wrong value proposition to your prospects

Finding the “Voice of the Customer” is the process of interviewing current customers and lost prospects to understand their pains, goals, and decision processes. By interviewing both types of people you can learn a lot about important factors that drive decision-making. 

Unfortunately, most companies look to the sales team as the conduit between customer and product when making important strategy and roadmap decisions. This is a dangerous precedent to set as it gives sales undue influence over the product roadmap and can result in major strategic decisions being made because of one or two isolated data points. Remember that the sales team is driven by short-term quotas and is usually not focused on the medium or long-term growth of the organization.  

Other companies rely on a small counsel or “brain trust” to make important strategic decisions. While each member of the brain trust is an expert in their own area (product, sales, customer success, marketing) they are often still removed from the end-user. They are not the buyers and users of your solution and have their own biases that will cloud their judgment.

Admittedly, planning and executing “Voice of the Customer” interviews is a challenging and delicate process, but it is absolutely vital to truly understand the value your product provides and how it should be positioned in the market. Hiring an external consultant experienced in this process is often the best way to get the facts and maintain objectivity through the process.

2. You aren’t communicating your unique value or product differentiation

Take a look at your website, your sales materials, and brochures. If they are filled with lists of product features and technical jargon then you may have a problem. To connect with your future customers, don’t hammer them with all the things your product does. Instead, create your content with the Voice of the Customer in mind. Put yourself in their shoes and think about what you care about when you shop for software. Customers are looking for solutions to their real problems, not lists of features.

If you haven’t crystallized your unique value proposition and differentiators, then you aren’t prepared to solve this problem. The Voice of the Customer process reveals customer pains, unique use cases, key stakeholders, and other important data. The results you gather should be directly applied to communicating your solution to their problems. You will likely find that your 5-page description of technical product features is not the compelling tool you think it is, and only serves to confuse your prospects.

The next aspect is to understand how prospects learn about solutions. Understanding this allows you to prioritize the materials you need and how to get them into the hands of your prospects. For example, in B2B SaaS you will often see the marketing team spending hard-earned money on Facebook and Twitter ads, but can you actually trace any of your closed deals back to either source? If you ask your prospects about how often they use Facebook and Twitter to learn about business solutions, you’ll get your answer. By identifying where your prospects hang out, what they read, who they trust, and how they shop, you can tailor your communication strategy to match the behavior of your customer.

Ultimately you should strive to create a shortlist of sales and marketing collateral that is value and use-case driven. This content can take the form of product datasheets, case studies, whitepapers, or blog posts and should reinforce your unique selling proposition. A potent blend of customer testimonials and consultative selling is a winning combination that will help jump-start revenue generation.

3. You can’t reach enough prospects who have the problem you solve 

Unless your product sells itself, your sales team is vital to maximize revenue. If sales doesn’t get enough quality leads and pursue them effectively, then two things will occur. 

1. The sales team will struggle to meet their quotas, and your company will miss revenue targets. 2. Your lead-to-close conversion rate will not be high enough to sustain company growth.

Velocity matters. You need an engine that can produce qualified prospects at an effective cost. Investors like to see customer acquisition costs (CAC) no higher than 30% of life-time value (LTV). Keeping sales costs low and scalable is important, which is why you need a data-driven SDR team that continually supplies your sales reps with qualified meetings. 

Unfortunately, hiring and training an SDR team is both time-consuming and expensive. By outsourcing your lead qualification function to a turn-key company, you can immediately start hunting for your ideal prospects. This frees up your sales team to focus on what they do best, selling your solution. 

The Voice of the Customer research, combined with potent, value-driven communications and collateral will arm your sales team with an arsenal of material they can use to effectively close the deals delivered by the SDRs. Your marketing team can also build on the research and share it with leads to help them progress through the funnel. With the right targeting, message, and materials, your close rates will rise. Your team will be talking to the right people in a language they understand about the problems they care about. 

Maximize revenue and never miss another target

Missing revenue goals often leads to a lot of finger-pointing and falling confidence.  When it happens repeatedly you need to take action to find the problem and correct it.  The building blocks of SaaS revenue growth aren’t magical, they require several inter-related skills and a scalable process. 

If your team is already running at full capacity, an external team can be the shot in the arm your business needs to get back on track. If you would like to learn more about how the SaaS Sales Accelerator can help increase revenue growth and drive qualified leads, contact us for a free assessment to learn if your company is a candidate. Email [email protected] or call (949) 357-0678.

Onboarding New Customers is Critical to SaaS Success

saas business model mckinsey

However, easy come, easy go.   The risk shifted to the software provider to deliver compelling value to capture the customer and hold onto them (and their recurring revenue stream) for as long as possible.  This progressive view of continuous value delivery is important to instill across your company.  Without attention to continuous value delivery, churn will likely steal away your hard-earned revenue.

One key process that is often underestimated and thought of after-the-fact is customer onboarding.  A bad customer onboarding experience will convert prospects to customers poorly.   Bad is friction in the process, lack of trustworthiness, setting expectations incorrectly, failure to make clear the outcome the prospect is looking for, and failure to deliver value very quickly.

In addition, as OpenView Partners points out in this useful guide about onboarding , the process begins as early as the ad the prospect clicked and the page they land on.   A marketing promise that disconnected from value demonstrated in the first moments using the product is a common error.  In fact, the promise of outcomes and expectation management begins at first touch, long before the user creates their own self-service account.

The Sudden Death of your Sales Heroes

saas business model mckinsey

  • - The importance of digital sales has doubled over that of traditional sales interactions since the onset of COVID-19.   The importance is measured for both customer preference and vendor preference on this point.
  • - Digital self-serve for order submission is now preferred significantly more by customers.  A preference for sales rep involvement is down dramatically .
  • - E-commerce share of overall B2B company revenue is up in all countries.  Up 29% in the US.   Most SaaS products could sell subscriptions online but many don’t have the digital sales and marketing maturity to put it in place. 
  • - Live chat is now seen as the most beneficial channel for researching suppliers.
  • - 65% of B2B decision makers believe the new sales model is as effective or more than prior to COVID-19.
  • - 79% are likely to keep the new model.   A scant 17% of companies were unlikely to keep the new sales model after a year.  

What’s Plan B? Maintaining B2B sales lead volume during a global pandemic

saas business model mckinsey

New SaaS Research: Hottest B2B Growth is in Mid-Market

saas business model mckinsey

Drive SaaS Sales with Product-Led Growth

saas business model mckinsey

What is PLG and why you should consider it in your SaaS Business Model

Why saas and plg are intrinsically linked, five traits of successful plg companies:, b2b vs enterprise saas: the critical distinction.

saas business model mckinsey

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Every CEO strives to maximize revenue, but at some point, they face the difficult challenge of missing a revenue target. The target may be s...

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