SaaS – Fuel, A McKinsey Company https://get.fuelbymckinsey.com Wed, 29 Jan 2020 20:31:19 +0000 en-US hourly 1 https://wordpress.org/?v=5.2.2 Does Your CLTV to CAC Ratio Stand Up? Does It Matter? – Infographic https://get.fuelbymckinsey.com/article/does-your-cltv-to-cac-ratio-stand-up-does-it-matter-infographic/ https://get.fuelbymckinsey.com/article/does-your-cltv-to-cac-ratio-stand-up-does-it-matter-infographic/#respond Sun, 01 Dec 2019 16:58:42 +0000 https://get.fuelbymckinsey.com/article/auto-draft/ Talking about LTV/CAC without clarifying which method you're using is a dangerous game.

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Software Pricing Pitfall #2: Settling For a Suboptimal Price Metric – Infographic https://get.fuelbymckinsey.com/article/pricing-pitfall-2-settling-for-a-suboptimal-price-metric-infographic/ https://get.fuelbymckinsey.com/article/pricing-pitfall-2-settling-for-a-suboptimal-price-metric-infographic/#respond Fri, 04 Oct 2019 19:09:23 +0000 https://get.fuelbymckinsey.com/article/auto-draft/ Price metrics are not a new concept. Defined simply as a scalable quantity to which one ties the price of a sale, they have been around in one form or another for as long as products have been sold.

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So what works for your team? Choose a metric that works. There are 5 Broad categories of price metrics. 

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Software Pricing Pitfall #2: Settling For a Suboptimal Price Metric https://get.fuelbymckinsey.com/article/pricing-pitfall-2-settling-for-a-suboptimal-price-metric/ https://get.fuelbymckinsey.com/article/pricing-pitfall-2-settling-for-a-suboptimal-price-metric/#respond Wed, 04 Sep 2019 23:09:58 +0000 https://get.fuelbymckinsey.com/article/auto-draft/ Price metrics are not a new concept. Defined simply as a scalable quantity to which one ties the price of a sale, they have been around in one form or another for as long as products have been sold.

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Boom Times for Pricing Metrics 

Price metrics are not a new concept. Defined simply as a scalable quantity to which one ties the price of a sale, they have been around in one form or another for as long as products have been sold. A price metric’s primary role is to allow a company to differentiate – to adjust prices to meet an individual customer’s (or group of customers’) willingness to pay. 

What is new is the breadth of price metrics that is now available for tech companies. 

In some cases, price metrics can almost transcend the field of pricing and become a key competitive differentiator. Several large markets have been disrupted by companies employing radical new price metrics. However, such creativity in price metrics is still more exception than the rule, and many companies succumb to the pitfall of not thinking beyond the status quo.

The options are so numerous we tend to think of five broad categories of price metrics rather than individual metrics:  

Seat based – metrics closely related to the number of people using the product
Usage-based – metrics related to how much or how frequently the product is used
Hardware-based – metrics based on the number of connected devices, or the amount of system resources required
Company business metrics – metrics based on the scale or performance of the customer (e.g., revenue, number of employees)
Success-based – metrics that align with the output or impact driven by the product (e.g., reduction in costs)

Startups Stuck in Their Seats

More than 20 years after the advent of the mainstream internet, pricing a product “per seat” – the metric closest to the license-based, legacy desktop software model – is still very common. In fact, the proportion of SaaS companies that use a variant of “number of seats” as their primary metric is 39%, making it the most common price metric category – according to a 2018 SaaS Survey by KeyBanc. 

While seat-based metrics can undoubtedly be the right choice for a subset of companies, it would be surprising if seats was the ideal metric for as many as 39% of SaaS companies. We frequently encounter startups that feel their seat-based models are not achieving their objectives. For many businesses, seats as metric fails to satisfy key price metric criteria:

  • Not linked to value – Consider an analytical product used by 100 users at an enterprise company, but with only 3 power users accounting for 95% of the usage. Beyond the initial 3 licenses, the value to the company would not increase consistently as more users are added.
  • Not scalable – Consider a tool aimed at a marketing team, which has remained the same size for 10 years, and shows no sign of changing. As the number of users is unlikely to increase, charging per user will likely never raise the revenue per customer, and so it is not a scalable metric for growth
  • Not auditable – How many times have people shared licenses (or credentials) with their colleagues for an online database? It can often be challenging to know how many users are truly using the product, and to set the price appropriately.

What seat-based models do have, however, is a higher degree of familiarity. This makes them easy to explain and implement, and therefore highly acceptable to the customer. So the very ubiquity of seats makes them the easy choice for companies without pricing expertise, which is often true of startups. In this way the selection is self-propagating. More seat models emerge, and seats beget seats.

Choose Value-Linked Metrics…

Still, does it really harm companies to price based on a metric that is not the best for their customers? The answer is yes. And in a number of ways. Most importantly, choosing the wrong price metric inhibits the ability to price differentiate. For example, if a company is selling some form of capacity when the buyer doesn’t value that metric, one of two things may happen:

  • Buyers will purchase fewer capacity units than intended, thereby pushing the purchase price down. 
  • Buyers will ask forthe needed amount of capacity for a lower purchase price, since they don’t want to pay the list price for the last few seats.

Either way, the buyer ultimately pays less than it is actually willing to pay. This was true of an online reference tool startup that priced its product based on concurrent user licenses (CULs) for their various content sets,  the expectation being that large Enterprises would purchase up to 8 CULs. Company research found that these enterprise clients were actually willing to pay the price levels that corresponded to eight CULs, and yet they purchased fewer than two CULs on average. Because the CUL metric was not value-based it did not work as a price differentiator, and customers were able to purchase a workable solution at a price significantly below their willingness-to-pay.  The vendor was missing out on signicant revenue it could have captured with a more value-based metric.

This can be avoided (or greatly mitigated) if pricing is based on a metric that is more strongly linked to the value that customers receive from the product. For example, a product that increases sales-win-rates might consider pricing on the customer’s baseline new business revenue, since the value realized will be a product of that revenue. A search engine might charge by the number of searches. An analytical tool might charge by the amount of analytical horsepower provided. Smart companies understand how they add value to the customers and align their commercial models.

Choosing the wrong price metric can also negatively affect the value proposition and sales confidence. A price metric, intentional or not, communicates to customers how a business adds value to them. As a result, choosing an inappropriate metric means misrepresenting the source of value creation, or at least not presenting it in the best possible light. This can complicate sales messaging and detract from the sales team’s confidence, ultimately leading to lower sales volumes and more frequent and dramatic discounting. 

… With Sufficient Predictability

One caution when choosing a highly value-based metric – ensure that it meets predictability requirements.  Usage-based metrics (e.g. API calls, # downloads, # site visits etc.), for example, are frequently seen as value-based, but they can be hard to estimate over time.  Even if the customer agrees that additional usage is value-linked and worth paying for in principle, tieing the price to an unpredictable metric results in unpredictable pricing. Budgeting is frequently important to customers, especially large enterprises, and uncertainty here can inhibit sales velocity. 

Predictability can be enhanced by either buffering against fluctuations – providing more usage for the same price, fixing price within a “band” of usage, and/or resetting price based on usage less frequently (e.g. annual price resets as opposed to charging on a monthly meter) – but all of these methods share the downside of reduced future upsell potential.  An unpredictable metric can still be the right choice overall, but should be chosen with visibility of these potential consequences, and with an execution strategy to mitigate them.

Unlock Significant Value

The impact of changing to value-aligned pricing metric is frequently immediate and dramatic. Consider the following examples from the public eye, as well as our own experience.

  • A cloud-based content management provider with rapidly declining growth implemented a new pricing metric which improved correlation with willingness-to-pay by over 10X, and resulted in an almost immediate 10% revenue increase.  
  • Through switching from seats to “active users,” an analytics provider managed to reduce churn by 3 percentage points and saw a large improvement in sales rep satisfaction.  
  • Mention, a social media monitoring tool, raised their average revenue per account by 269% by switching from seats to the number of “alerts” that an organization configures.  
  • An appliance-based network software vendor realized an 8 percentage point  YoY revenue  growth rate increase through switching from a traditional hardware-linked metric to a measure of network connection speed
  • Even Google is an example here, since a big part of its success came from changing the standard price metric for online advertising from cost-per-impression to cost-per-click.

How to Pick the Right Metrics 

The way to find a price metric that could deliver the kinds of results mentioned above is through a combination of brainstorming and evaluation:

Brainstorm possible metrics
Use the categories defined within this article and attempt to think of several metric options that would fit in each. Look to companies in adjacent industries for inspiration. Consider how the company creates value for customers (i.e., does value increase per user?  Per session? Per gigabyte?) and look for metrics that align with the amount of value created.

Evaluate the shortlist
Teams should evaluate the shortlist of metrics against the 5 key criteria for a price metric:

  1. Link to Value – A great price metric aligns with the amount of perceived value that customers receive from the product. If customers agree that as the metric increases, they get more value from the product, they will not question that the metric is a sensible basis for pricing.
  2. Scalability – Ideally, a price metric provides a pathway to future growth.  If a metric is scalable, it is expected to grow following the initial sale, and so tying it to growth will help increase revenue per customer over time.
  3. Predictability – Being able to budget is important to customers, so a metric that does not allow them to predict what their prices will be in the short- and long-terms can be a barrier to adoption.
  4. Auditability – To prevent abuse of the system and/or ambiguity around prices, a metric should be able to be objectively measured, without relying primarily on the customer to provide the relevant information.  
  5. Acceptability – Finally, for the metric to be successful it must be acceptable to the customer. Even if the metric satisfies the above four criteria, if customers don’t feel it is fair to tie this metric to price, the customers may reject the pricing model, hampering initial sales velocity.

Rigor and confidence can be added to this step by launching customer research to achieve an ‘outside-in’ perspective of the metrics.

Select the best overall metric(s)
Given a business’ objectives and strategies, some of the criteria defined above will be more important than others. Startups should agree on which criteria are most important and create a weighted performance score for each metric.  The metrics with the top overall scores will be your best candidates.

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It is worth mentioning that, having picked your preferred metric, you still have work to do in (a) deciding how price scales with that metric, and (b) verifying through careful revenue modeling that converting to the new metric will be revenue positive. But aligning on an optimal metric is undoubtedly a hugely important step that is trodden too infrequently.

Choosing a price metric doesn’t have to be difficult or complicated. But for the reasons we have discussed, startups shouldn’t just make the easy or default choice. By being thoughtful and taking these few simple steps, startups can choose a price metric that can be a critical lever to accelerate growth.

In our next article in this series, we will be exploring the startup Pricing Pitfall #3: off-target value communication.

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Blockchain Stalls, Synthetic Fraud, and AI Helping Humanity https://get.fuelbymckinsey.com/article/blockchain-stalls-synthetic-fraud-and-ai-helping-humanity/ https://get.fuelbymckinsey.com/article/blockchain-stalls-synthetic-fraud-and-ai-helping-humanity/#respond Thu, 24 Jan 2019 19:53:22 +0000 https://get.fuelbymckinsey.com/article/auto-draft/ Do You Even Blockchain? Blockchain buzz continues to drive intense interest in experimentation. But that fervor has cooled off significantly. Axios reported an 80% drop in the use of “blockchain” on corporate earnings calls in 2018. And a recent McKinsey article outlines “Blockchain’s Occam Problem.” The authors state that blockchain has failed to advance out of its […]

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Do You Even Blockchain?

Blockchain buzz continues to drive intense interest in experimentation. But that fervor has cooled off significantly. Axios reported an 80% drop in the use of “blockchain” on corporate earnings calls in 2018. And a recent McKinsey article outlines “Blockchain’s Occam Problem.” The authors state that blockchain has failed to advance out of its early “pioneering stage” and the key to finding real value in blockchain is applying it when it’s the simplest solution available.

From the article:

“There is a clear sense that blockchain is a potential game-changer. However, there are also emerging doubtsA particular concern, given the amount of money and time spent, is that little of substance has been achieved. Of the many use cases, a large number are still at the idea stage, while others are in development but with no output. The bottom line is that despite billions of dollars of investment, and nearly as many headlines, evidence for a practical scalable use for blockchain is thin on the ground.”

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Machine Learning vs Synthetic Fraud

One of Fuel’s most popular articles last year was about the emerging $20 billion dollar ID verification-as-a-service market. The need for innovation in biometric ID verification remains important. A recent McKinsey article states that “synthetic ID fraud” is now the fastest-growing form of financial crime in the USA. 

From the article: “Synthetic IDs are created by applying for credit using a combination of real and fake, or sometimes entirely fake, information. The application is typically rejected because the credit bureau cannot match the name in its records. However, the act of applying for credit automatically creates a credit file at the bureau in the name of the synthetic ID, so the fraudster can now set up accounts in this name and begin to build credit.”

The authors propose an approach that incorporates machine learning to uncover critical third-party data to verify if the info given matches that of a real person.

How AI Can Help Humanity

The World Economic Forum has a short write-up of McKinsey Global Institute research on how AI can help humanity. The 160 social-impact use cases are framed across the 17 UN sustainable development goals – aimed at helping hundreds of millions of people.

Among the examples highlighted in the research:

The MGI research concludes: “What we found is that AI could make a powerful contribution to resolving many types of societal challenges, but it is not a silver bullet – at least not yet. While AI’s reach is broad, development bottlenecks and application risks must be overcome before the benefits can be realized on a global scale.”

Please “Join Fuel” (above) and follow us on LinkedIn and Twitter for more insights.

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Product Managers: In Demand and … Undervalued? https://get.fuelbymckinsey.com/article/product-managers-in-demand-and-undervalued/ https://get.fuelbymckinsey.com/article/product-managers-in-demand-and-undervalued/#respond Mon, 07 Jan 2019 19:53:41 +0000 https://get.fuelbymckinsey.com/article/auto-draft/ Product managers play an increasingly central role within any software startup. Research led by Chandra Gnanasambandam, Martin Harrysson, Shivam Srivastava, and Vaish Srivathsan on the McKinsey Product Management Index shows PMs are deeply involved in almost all aspects of product success. The same research shows that despite PMs being a top priority for software CEOs, they are often neglected when […]

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Product managers play an increasingly central role within any software startup. Research led by Chandra GnanasambandamMartin Harrysson, Shivam Srivastava, and Vaish Srivathsan on the McKinsey Product Management Index shows PMs are deeply involved in almost all aspects of product success.

The same research shows that despite PMs being a top priority for software CEOs, they are often neglected when it comes to talent management. “The Product Management Talent Dilemma” explores this paradox between the rising importance of PMs and the under-investment in resources and systems dedicated to finding and developing high-performing ones. The authors outline four specific levers software companies can use to correct this imbalance and formalize a system for recruitment and growth:

  1. Articulate a leadership development model for product managers
  2. Enable ways for PMs to have continuous growth and learning opportunities
  3. Design an end-to-end learning journey for PMs
  4. Make hiring a strategic priority. Top senior PMs report spending up to 5% of their time on recruiting

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The full article contains further insights from the McKinsey Product Management Index and, among other things, covers the five core capabilities and enabling structures that develop top-tier PMs.

For more insights, please “Join Fuel” (above) and follow us on LinkedIn and Twitter.

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Pricing Pitfalls: The Four Most Common Packaging Mistakes https://get.fuelbymckinsey.com/article/pricing-pitfalls-the-four-most-common-packaging-mistakes/ https://get.fuelbymckinsey.com/article/pricing-pitfalls-the-four-most-common-packaging-mistakes/#respond Mon, 03 Dec 2018 20:00:51 +0000 https://get.fuelbymckinsey.com/article/auto-draft/ The Rise of Tiered Packaging Several years ago, much of the guidance with packaging was just “make sure you create packages!” This sounds almost redundant, but it spoke to the fact that we frequently observed companies using the monolithic “one size fits all” approach. The implicit message to the customer is: This is our product. Take […]

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The Rise of Tiered Packaging

Several years ago, much of the guidance with packaging was just “make sure you create packages!” This sounds almost redundant, but it spoke to the fact that we frequently observed companies using the monolithic “one size fits all” approach. The implicit message to the customer is: This is our product. Take it or leave it.

Thankfully, we see this far less frequently today, particularly with SaaS companies. Most startups we encounter have adopted a “Good, Better, Best” (GBB) approach. This means creating several tiers of packages which vary in terms the price level and the amount or quality of items included (features, services, usage levels, etc.).

The Many Benefits of Good, Better, Best

Adopting the GBB approach has many benefits. Since customers typically dislike “take it or leave it” offers for anything other than very simple products, providing choices can make a customer more likely to buy. If nothing else, moving from a single offering to a GBB approach will likely increase velocity of sales.

However, GBB can also offer a highly-effective method of price differentiation. In swapping one price level for three (usually), you can accomplish two things. First, you make your product viable for customers at the lower end, who would not have purchased it previously (therefore adding sales volume). Second, you create a higher price point to monetize customers who would value a premium offering. All of this equates to more value capture at the initial sale. These packages can then even be used to grow your base business through upselling customers from basic to premium packages. It’s encouraging that we’re seeing more innovative GBB models in the startup community.

There are many other approaches to packaging. Use-case and buying center-based strategies can be effective for more mature companies selling to enterprises. But GBB is simple and readily accepted by customers. A GBB model – when well designed – is a highly-effective packaging strategy.

The Four Frequent Flaws in GBB Design

The key words in the above sentence are “when well designed.” The reality is that while many startups now realize the benefits of GBB, few have taken steps to create a robust approach. We commonly hear “we didn’t put a lot of thought into our packages.” We estimate that this oversight translates to a loss of 5-15% percentage points of revenue growth a year.

In order for a GBB system to work effectively for both price differentiation and sales velocity, GBB packages must be designed with well-defined customer segments. Each package should provide the target segment with a product it will be satisfied with, at a price it is willing to pay.

Customers vote with their wallets. The clearest indicators your packaging strategy is flawed will be the buying choices your customers make. If the distribution of package purchases does not match your expectations or desires (e.g. 75% of customers purchasing “good,” when you forecasted 40%) or your sales reps are consistently unable to upsell customers to higher-level tiers, you can be confident your issues lie within your packaging strategy.

The specific packaging issues we see most frequently are outlined below:

(P Axis = Price; V Axis = Value)
  • Too Much in the Base – The base package is just too good. The vast majority of customers are happy with what is included in the base package, and they don’t value the extra offerings in the higher-level packages enough to justify an upgrade. The majority of the business then shifts to the entry price point, which drops revenues unnecessarily.
  • Decoy Choices – A company has followed the conventional wisdom that the goal of GBB is to draw customers to the middle version. Now the good version is too light. And the best version is so incremental in value to the better version, that the middle option is the only realistic choice. In this situation, the other packages serve only to make the middle option look better. You will get the sales velocity benefit of packaging, but nothing more.
  • Unrealistic Comparisons – The difference in price of the packages so large that any differences in value between packages are immaterial. It’s easy to imagine a customer choosing between packages costing $200, $500, or $750 a month. But can you imagine them truly considering options that cost $200, $2,000, and $20,000? When this is the case, the customer doesn’t really have a genuine choice anymore. They will feel forced into the one option designed for them. Now the benefits of having a choice-based packaging system erode.
  • Too Many Sources of Difference – Tiers do not work when the packages differ across too many attributes, particularly attributes that cut across different and unrelated use cases. It is likely that a customer will attach value to some of the sources of package differentiation, but not to all of them. This can result in the customer objecting to paying the premium for the higher-level package, since they feel that much of that premium is for items they don’t need (this effect is particularly marked when the price difference between packages is also high).

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Best Practices for Designing the Good, Better and Best Tiers

The solutions to poorly-tiered packaging are not complicated, but require a solid understanding of your customer segments, needs, and willingness-to-pay. All of this can be obtained through robust customer and prospect research.

  • Align on a suitable base – Developing a base (“good”) package, with the necessary minimumfeatures, is a critical step in the design journey. Price differentiation is about giving your customers something that they are satisfied with at a price they are willing to pay. The segment of your customers with the lowest willingness-to-pay should be satisfied with the base package. Thus, the base package should be the lowest spec package you can produce while preserving this satisfaction. All items which are “table stakes” should be included, along with any low-value items that would be a distraction while selling.
  • Tier by only the key value drivers – The next step is to determine what are the few key value drivers that truly drive value perception to the segments with higher willingness-to-pay. These value differentiators can be comprised of multiple features, but the breadth of overall functionalities or capabilities that they enable should be limited. Less is more in this case, since this will allow sales and marketing to build a clear value story around the higher tier packages and will make the upsell case more compelling.
  • Build in up-sell triggers – You can further strengthen the upsell pathway by incorporating thresholds into your package design. Placing caps on capacity or usage by tiers can drive upsell to the next tier when the customer’s needs outgrow the current tier. This is a particularly effective strategy when the threshold is the customer’s amount of usage of a highly valuable feature or function, since the up-sell trigger will then be self-selected and a natural reflection of increased value consumption from the product.
  • Consider scaling prices separately – Large price differences across packages are often primarily driven by companies trying to address large differences in customer scale and willingness-to-pay through the packages alone. For example, “we will make our ‘best’ version focused on Enterprises, and so will put capacity constraints on the ‘better’ version.” As mentioned above, this creates unrealistic choices. A better approach can be to remove ‘scale’ factors from the packages (make packages vary by quality components alone) and use a price metric to scale the price of each package to the customer (for example, package A may cost $500 to a customer with 500 employees, but $5,000 to a company with 100,000 employees).
  • Break out niche functionality – Sometimes certain features or functionality will be valued very highly by a small portion of customers. However, unless this group happens to be the highest willingness-to-pay segment that you’re targeting your “best” package towards, these features do not belong in a GBB framework. Similarly, if these features address very different use cases to the core product functionality, their inclusion in the GBB framework could cloud the value stories. The best practice is to monetize these niche features separately as add-ons instead.
  • Price the tiers to value delivered – For most buyers (especially B2B), low-priced offerings signal poor product quality. This can create a perception of risk, and so bring doubt into the purchase process. Therefore, for sales velocity as much as value capture, it is important to price each tier at an appropriate level for the amount of value delivered.

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Although more detailed decisions will need to be made, following these simple guidelines around pricing will help startups avoid falling into the common pitfalls of ineffective good, better, best packaging.

In our next article in Pricing Pitfalls, we will be exploring the next startup pricing challenge – selecting an undifferentiating price metric. You can email the authors at Fuel@McKinsey.com for more information. And please follow Fuel on LinkedIn and Twitter for more pricing insights.

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Don’t Get Blindsided Integrating a SaaS Company https://get.fuelbymckinsey.com/article/dont-get-blindsided-integrating-a-saas-company/ https://get.fuelbymckinsey.com/article/dont-get-blindsided-integrating-a-saas-company/#respond Tue, 14 Aug 2018 19:04:51 +0000 https://get.fuelbymckinsey.com/article/auto-draft/ Programmatic mergers and acquisitions (M&A) are a critical element of startup growth, as shown in McKinsey’s previous work “grow fast or die slow.” Most top performing SaaS companies need to extend growth by bulking up their product portfolio, bookings growth, market share, TAM, or talent and technology stack. Shareholder return-based studies suggest that programmatic M&A leads […]

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Programmatic mergers and acquisitions (M&A) are a critical element of startup growth, as shown in McKinsey’s previous work “grow fast or die slow.” Most top performing SaaS companies need to extend growth by bulking up their product portfolio, bookings growth, market share, TAM, or talent and technology stack. Shareholder return-based studies suggest that programmatic M&A leads to above average outcomes versus other M&A approaches.

Some SaaS companies have built strong M&A capabilities in this arena to become successful programmatic acquirers. If you look deeper at what top performing companies believe really separates the lowest and highest performers in M&A value capture, it is their ability to do “integration planning and execution,” as noted by the largest delta in the graphic below:

Global M&A Capability Building Survey, 2015. The online survey garnered 1,841 responses from C-level and senior executives.

Contemplating their first major acquisition can be a very stressful experience for a SaaS company CFO and/or CEO. Aside from whether it is the right target, or whether to proceed now versus later, or if the price is right – a big driver of success hinges on how well integration planning and execution is done. Yet many SaaS companies have no M&A team in place, so they are left scrambling to estimate the budget for integration efforts and activities, which can be hard to predict and plan for, much less having the capabilities and capacity to get the integration done.

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At Fuel, we find a common concern among SaaS companies is how much to budget for post-merger integration costs after that first big acquisition. These costs represent the one-time, non-recurring costs that companies will spend to rationally blend products, sales processes, operations, marketing efforts, brand, people, cultures, systems, and tools.  These are not the one-time transaction costs for the deal that sell-side investment bankers, M&A lawyers, and financial due diligence accountants earn.  These are the expenses borne both by internal employees and 3rd party consultants.

In order to better understand these costs, the Fuel team conducted an analysis on buy-side M&A deals in the SaaS industry. We reviewed 24 deals where the data was publicly available to calculate the implied one-time, non-recurring acquisition integration costs as a function of (1) acquired headcount and (2) purchase price paid.

Our analysis estimates that public SaaS companies will spend between:

  • “Per capita”basis: ~$18 to 33k per acquired FTE in one-time, non-recurring acquisition integration costs
  • “Deal value” basis: ~1.5 to 2.1% of the purchase price on one-time, non-recurring integration costs

For example: If a SaaS company is acquiring a startup with 70 full-time employees, our model estimates it would likely pay between $1.3 and $2.3 million in one-time, non-recurring costs to integrate the company on a “per capita” basis. On a deal value basis, a $300m acquisition implies a SaaS acquirer will spend between $4.5 and $6.4m for one-time, non-recurring integration costs.“Having a clearer idea of the true costs of integration should give SaaS leaders the sense of what value needs to be captured from a deal. ”

Having a clearer idea of the true cost ccs of integration should give SaaS leaders the sense of what value needs to be captured from a deal.

The $3-4m difference between ‘per capita’ and ‘deal value’ costs is because we used SaaS historical deal data to approximate the actual costs, so these estimates are via a calibration method. True costs will vary based on other factors: the negotiated purchase price, or if you have a full-time M&A integration team in house (where these costs are already baked into your recurring operating expenses). See the table below for an idea of the ranges within the companies we analyzed:

Source: Fuel, A McKinsey Company analysis of public data from 24 buy-side M&A deals in the SaaS industry between 01/2014 and 05/2018

Effective M&A integration can be challenging. It is wise for SaaS CFOs to budget on the higher-end of this spectrum for their first acquisition. Mistakes will be made. Hidden costs will emerge. But once muscle memory is developed from a few acquisitions and some scale, you can and should move down to the lower end of the integration cost spectrum.

Having a better understanding of the expected costs of integration, based on publicly disclosed, historical cost from past acquisitions in SaaS, will give C-level leaders the confidence to set aside adequate budget to ensure the proper resources are in place to achieve successful integration and to capture their fair share of benefits and value creation inherent in the acquisition.

Email Junaid or Oleg if you have any questions or want to discuss this article further. And follow Fuel on Twitter and LinkedIn for more SaaS insights.

The post Don’t Get Blindsided Integrating a SaaS Company appeared first on Fuel, A McKinsey Company.

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Pricing: The Secret Weapon You Haven’t Thought About https://get.fuelbymckinsey.com/article/pricing-the-secret-weapon-you-havent-thought-about/ https://get.fuelbymckinsey.com/article/pricing-the-secret-weapon-you-havent-thought-about/#respond Fri, 27 Apr 2018 19:17:50 +0000 https://get.fuelbymckinsey.com/article/auto-draft/ In our experience, there are several barriers to pre-IPO companies optimizing their pricing, and one of the most prevalent is the lack of firm evidence that pricing is not already optimized.  The reason?  Successful startups typically exhibit huge growth rates, and nothing hides opportunity better than success.  Even if you suspect your pricing isn’t perfect, […]

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In our experience, there are several barriers to pre-IPO companies optimizing their pricing, and one of the most prevalent is the lack of firm evidence that pricing is not already optimized.  The reason?  Successful startups typically exhibit huge growth rates, and nothing hides opportunity better than success.  Even if you suspect your pricing isn’t perfect, how would you know? And if your results are great anyway, why should you even care?

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The truth is that a detailed look at customer level sales data can often expose not only whether you have a pricing issue, but also what kind of pricing issue you have.  The trick is knowing what to look for – what analyses to run and how to interpret the results.  And you should care, because we have shown that improving your strategic and tactical pricing execution typically adds an extra 10-15 percentage points of revenue growth to even rapidly growing pre-IPO companies.  Capturing this opportunity requires you to first know there is an opportunity to capture, but many startups do not have the time or experience necessary to run the necessary diagnostics.

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Are you getting the most out of your pricing? Take our Pricing Fuel 5 Checkup to find out.

Try It Out

To help the startup community capture value through pricing, we at Fuel by McKinsey are offering pre-IPO companies an opportunity to get a Pricing Quick Diagnostic for free for a limited time period.  If you provide us with 2 years of monthly sanitized customer-level revenue data1, we will provide you with 3 key charts that will help identify opportunities for you to inflect your business with pricing improvements.  You’ll also receive a guide to interpreting your results.

As an example, we recently conducted a similar analysis for a SaaS company growing at >130% per year.  We determined that the company’s packaging scheme was preventing upsells, and that the company was ineffectively monetizing different customer segments.  Having realized these shortcomings, the company has pledged to address these issues and capture the value they are missing.

Learn more about our Pricing Quick Diagnostic here or Register Now.

Questions? Email us at fuelpricingqd@mckinsey.com.  We look forward to meeting you and identifying your pricing opportunity.

The post Pricing: The Secret Weapon You Haven’t Thought About appeared first on Fuel, A McKinsey Company.

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Channel Partnerships: Proceed With Caution https://get.fuelbymckinsey.com/article/channel-partnerships-proceed-with-caution/ https://get.fuelbymckinsey.com/article/channel-partnerships-proceed-with-caution/#respond Fri, 23 Mar 2018 19:22:37 +0000 https://get.fuelbymckinsey.com/article/auto-draft/ Conventional wisdom holds that channel partnerships can be a cost-effective way for SaaS companies to expand their reach and acquire more customers. But these relationships may come with significant costs—channel partners may not have the right incentives to push your product and they are difficult to monitor. Our analysis shows that SaaS companies considering channel […]

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Conventional wisdom holds that channel partnerships can be a cost-effective way for SaaS companies to expand their reach and acquire more customers. But these relationships may come with significant costs—channel partners may not have the right incentives to push your product and they are difficult to monitor. Our analysis shows that SaaS companies considering channel partnerships should proceed with caution. They are useful when companies need to grow beyond their internal capabilities, but in the long run they are not the best use of precious sales and marketing dollars.

In our post entitled “Want to Accelerate Value Creation?” we explained why we think growth efficiency—the net new ARR each dollar of sales and marketing generates—is an important and useful metric for SaaS companies. We’ve used that metric—along with detailed sales and marketing data from nearly 200 companies in our SaaSRadar database—to test several common SaaS sales and marketing practices. (See, for example, our post on “land and expand.”)

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As the chart above shows, channel partnerships are a mixed bag. We found that companies in our database that relied heavily upon channel partnerships to acquire new customers generally grew less efficiently. SaaS companies that did no marketing through channel partners had a 1.70 growth efficiency score, on average, while companies that relied on partners for 10% or more of their new customer acquisition only had a 0.71 growth efficiency or lower. Looking at new logo growth, however, yields a different picture. The companies in our survey that grew their new customers the fastest over a 12-month period were those who acquired 1-5% of those customers through channel partnerships. And with more channel partnerships, the data in our survey becomes a little noisy. This suggests that channel partnerships can be useful to achieve certain key growth objectives in the lifecycle of a company, but that they shouldn’t be relied upon too heavily at all times.

The post Channel Partnerships: Proceed With Caution appeared first on Fuel, A McKinsey Company.

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Land vs. Expand: Finding the Right Balance for Your Salesforce https://get.fuelbymckinsey.com/article/land-vs-expand-finding-the-right-balance-for-your-salesforce/ https://get.fuelbymckinsey.com/article/land-vs-expand-finding-the-right-balance-for-your-salesforce/#respond Fri, 02 Mar 2018 20:24:01 +0000 https://get.fuelbymckinsey.com/article/auto-draft/ We all know that landing any new customer is something to celebrate, particularly because you can then “land and expand,” using sales and marketing resources to grow revenue from that same customer. But how much precious salesforce time should go to cross- and up-selling existing customers, versus new logo acquisition? We answered that question using SaaS […]

The post Land vs. Expand: Finding the Right Balance for Your Salesforce appeared first on Fuel, A McKinsey Company.

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We all know that landing any new customer is something to celebrate, particularly because you can then land and expand, using sales and marketing resources to grow revenue from that same customer. But how much precious salesforce time should go to cross- and up-selling existing customers, versus new logo acquisition? We answered that question using SaaS Radar, Fuel By McKinsey’s proprietary database of nearly 200 SaaS companies. Our analysis suggests that companies need to take a Goldilocks approach—not too little, but not too much. Companies that devote about 10-25% of their sales resources to farming instead of hunting do best.  If you devote more than that, the upside is less than it would be from devoting those resources to new customer acquisition, and the opposite is true if you invest less than 10%.

Source: Fuel By McKinsey SaaSRadar.

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In our post “Want to Accelerate Value Creation?” we described our approach to determining how efficiently a SaaS company is growing—we measure how much net new ARR each dollar of sales and marketing generates. Using that metric, we determined that if more than 25% of your customers are upsold in a quarter your growth efficiency is over 1.6. If less than 10% of your customers generate new revenue for you in a quarter your growth efficiency is less than 1; this means you are not generating sufficient new ARR to cover your sales and marketing expenses.  At the same time however, since upselling distracts from new customer acquisition, it is important to find the right balance. Your growth efficiency is at its optimal level when you invest between 10-25% of your existing sales resources on upselling and cross selling, as seen in the chart above.  This doesn’t mean you shouldn’t invest in customer success, but your salesforce should be spending the majority of its time on new logo acquisition.

The post Land vs. Expand: Finding the Right Balance for Your Salesforce appeared first on Fuel, A McKinsey Company.

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