My Take on the Zuora Acquisition

On October 17, 2024, Zuora announced its acquisition by Silver Lake, a private equity firm, for a total of $1.7 billion. The acquisition was not unexpected. My former employer had already announced on April 17 that it was “exploring strategic options, including a sale”. The buyer was also not a surprise, as Silver Lake had already invested $400 million in Zuora on May 9. Acquiring the remainder of the company cost them only $1.3 billion. 

What is surprising is the price. 

The offer of $10 per share represents a meager 6% increase above the previous day's closing price of $9.42. Yikes! As a shareholder who has been holding underwater shares from an ESPP purchase over 3 years ago, I find this quite disappointing. Sure, you might say that an ARR multiple of 3.7 is what PE companies pay (Zuora expects to make $455.5-461.5 million this year). But that doesn’t make it any better for the investors. The stock closed at $9.91 on Friday which signals that many other investors are unimpressed. 

How did Silver Lake manage to secure such a lucrative deal? 

Zuora pioneered subscription billing and remains the company to beat in this space. It boasts an impressive roster of customers, a highly knowledgeable team, and a broad range of capabilities that none of its competitors can match today. Yet, Zuora’s stock has remained stuck in single digits for almost three years, with no upward movement. 

This stagnation isn’t due to poor execution. The management team has lately consistently exceeded earnings expectations quarter after quarter. The issue wasn’t execution—it was strategy. 

A subscription billing platform operates between orders, payments, and the general ledger—in other words, between CRM, payment processors (PP), and ERP. These are Zuora’s strategic touchpoints; its inputs and outputs. When Zuora first started, it was the only game in town. However, today, all those vendors have added subscription billing capabilities, which puts pressure on the demand for Zuora. Salesforce (CRM), MS Dynamics (CRM), Stripe (PP), Gotransverse (PP), SAP (ERP), and NetSuite (ERP)—they all offer subscription billing today and they don’t need Zuora. 

When you’re being squeezed by all your strategic touchpoints, you must find a way out. One strategic option is to push back by adding capabilities that encroach on their turf. That’s what Zuora did by introducing solutions like CPQ, payment recovery, and revenue recognition. Unfortunately, this fragmented approach didn’t succeed, especially when facing much larger competitors like Salesforce, Stripe, SAP, and Oracle. In such situations, the next strategic move is either to find a new direction for expansion—which, arguably, wasn’t available—or to specialize. 

That’s exactly what Zuora did by deepening its focus on the manufacturing and media sectors. It even acquired a paywall vendor Zephr to strengthen its media solution. However, most manufacturing companies are not good at selling software or data subscriptions, and most media companies already know how to do subscription billing and deal with more existential problems. Focusing on verticals was the right move, but Zuora probably chose the wrong ones. It’s easy to critique in hindsight, but selecting other verticals like insurance, financial services, healthcare, or utilities might have been a better strategy for verticalization. Maybe. 

In the meantime, Zuora began missing out on many software market opportunities, while software is the largest market for subscription billing. Software companies need billing solutions from the early stages as tiny startups, but Zuora’s platform, designed to handle some of the most demanding enterprise billing scenarios, is too complex for startups. What these companies are looking for is a simple billing solution that can be integrated with just a small snippet of code, like the solutions from Stripe or Metronome.  

Zuora was also slow to respond to the rise of usage-based billing, which is a hot topic these days. Whether usage billing is the future remains to be seen, as most customers seem to hate it. However, its emergence created an opening for upstarts like Metronome, Orb, M3ter, and Tioga—the latter eventually acquired by Zuora. Unfortunately, that move came too late to make any significant impact. 

Moving down-market is nearly impossible for an enterprise software vendor; it’s difficult to simplify software built for large enterprises (the opposite is somewhat easier). Acquiring an SMB vendor to target the SMB market was likely not an option for a relatively small publicly traded company with not that much cash on hand. It seems like Zuora wasn’t left with many strategic alternatives here. However, failing to act quickly enough on usage-based billing was another key strategic misstep. 

Out of strategic options, Zuora publicly put itself up for sale. Silver Lake quickly seized the opportunity with an initial investment, and since no strategic buyers emerged, Silver Lake ended up acquiring the entire company a few months later. The modest 6% premium reflects the strategic predicament Zuora found itself in. Silver Lake got a good deal, and now Zuora will need to figure out its strategy under private equity ownership, which is not known for fostering growth through innovation investments. 

I wish Zuora well. It’s a great company that stands as a shining example of category creation, thought leadership, and solid execution. However, I’m unhappy about the stock price. 

Why I Joined Egnyte

Yes, after two years of working on my own as an independent consultant, it happened. One of my clients made me an offer to join their company, and I decided to take the leap. Why did I do that? 

"Lubor, I thought you were done with this space!" said Marko Sillanpaa from Gartner when I joined a recent briefing. Marko and I go way back to our Documentum days. 

Well, it’s true. After spending nearly 15 years in content management companies like Vignette, Documentum, and OpenText, I was starting to get bored. For years, I had been trying to convince customers to manage their content to avoid compliance, governance, and litigation risks. But, aside from companies in highly regulated or litigious industries, most didn’t care. 

Things became even clearer when the new upstarts began pushing Enterprise File Sync and Share (EFSS). In the spirit of "consumerization" and "enterprise 2.0", they claimed that IT was becoming irrelevant, and many companies decided to stop worrying about how their content was managed. Employees were indiscriminately sharing files straight from personal drives. It was madness, but I knew it would take time for people to realize that. 

So, I left the enterprise content management (ECM) world and ventured into business applications, to finally get the experience of marketing to business buyers. Funnily enough, the companies I worked for had a horrible way of sharing and managing content. Their content chaos was a massive productivity drain, and they didn’t even know about it. 

But, I kept an eye on the content platforms. 

For a while, it seemed like nothing would change. Most of the old vendors faded away, and EFSS 'boxes’ became just as boring once they started selling to enterprises. They kept talking about compliance on and on, but no one cared. Content was seen as more of a liability than an asset, with "secure collaboration" being the most exciting positioning they could muster. 

Then, generative AI arrived. 

It quickly became clear that while ChatGPT is awesome, for business use, it needs to work with a company’s private, often sensitive, content. That changed the game for content platforms since they own the content repositories. Even if a lot of content still lives in personal drives, content management suddenly matters again. The focus shifted from reducing risk to boosting productivity. Now that’s cool—AI used for something truly useful! I want to be part of that. 

When I started working with Egnyte as one of my clients, I found a company with leading-edge cloud technology, with all the bells and whistles you’d expect from a modern content platform. Unlike EFSS vendors, Egnyte has always focused on control and security, eliminating duplicates, data leaks, and privacy issues. This becomes crucial when applying generative AI to private company content. Random duplicates can lead to incorrect answers, which isn’t acceptable in business. Egnyte figured this out long ago. 

On top of that, Egnyte has powerful and unique capabilities for managing highly complex content with massive files like CAD files, BIM models, and Adobe creative projects. I saw a company with amazing technology, strong prospects, a great team, good culture, and solid financials. I knew I could make a difference here. So, I said yes.  

Yes, I’m running product marketing again, which is what I love. I’m diving deep into the technology, working closely with product teams, and using all my marketing craft to tell Egnyte’s story. There’s a lot of work ahead, but the opportunity is huge.

I’m excited to be back in the content management space. It’ll be fun reconnecting with industry analysts like Marko Sillanpaa, Cheryl McKinnon, Craig LeClair, Marci Maddox, Alan Pelz-Sharpe, Dan Lucarini, and others. I might check in with AIIM, where I served on the Board for five years, to see what they’re up to. And I’m really looking forward to meeting with customers in person. 

It’s great to be back. We’re just getting started! 

Mike Lynch, Autonomy, and Incredible Coincidences

My story today is incredible. It’s just too wild and hits too close to home to ignore. It’s about Mike Lynch, Autonomy, and a string of coincidences so unbelievable that not even a Hollywood screenwriter could dream them up. 

So, let’s start at the beginning.

Autonomy was founded in 1996 in Cambridge, UK, by Mike Lynch, David Tabizel, and Richard Gaunt. The company went public in 1998 at £0.30 per share on EASDAQ, Europe’s version of Nasdaq. Autonomy’s core product was an enterprise search technology, called IDOL (Intelligent Data Operating Layer), which supposedly used a pattern recognition technique based on the Bayesian algorithm. Keep that name "Bayesian" in mind—it’s going to pop up again later.

Sailing yacht Bayesian

Over time, Autonomy expanded its portfolio by acquiring a range of companies, including Verity (search), Zantaz (email archiving), Meridio (records management), Interwoven (web content management), iManage (legal document management), and Iron Mountain Digital (archiving and e-discovery). They even scooped up the content solutions from Computer Associates. Through these acquisitions, Autonomy became a major player in the content management space, going head-to-head with giants like EMC/Documentum, IBM/FileNet, Microsoft SharePoint, and OpenText.

Around 2009-2010, Autonomy became a significant challenge for me while I was leading product marketing at OpenText. It wasn’t that we were losing many deals to them—Microsoft was actually the much tougher competitor in that regard. But Autonomy was winning the battle for mindshare and thought leadership. Their stock was performing much better than ours, and this caught the attention of our Board and executive team. We spent countless hours analyzing and sometimes agonizing over it.

The truth is that Autonomy had a great narrative. Its "meaning-based computing" story suggested that instead of managing and organizing your digital content, you should just focus on how to find it—compelling, even if misguided. It sounded great: don’t worry about how you store, secure, and use your content. As long as you can find it, leave it wherever it is, no matter how it’s managed. This was the AI hype long before AI became a thing! 

As a marketer, I still admire the message for its impact and consistency. Yeah, I'm still a little jealous and I've learned a few lessons from it. Autonomy’s “meaning-based computing” portfolio was cleverly packaged into three pillars: “Protect” (archiving, compliance, e-discovery), “Power” (enterprise search), and “Promote” (WCM and e-commerce). CEO Mike Lynch loved adding a scientific spin, often referencing the 18th-century mathematician Thomas Bayes. He even included Bayes’ theorem in the company’s 2010 annual report—without any explanation. It didn’t make much sense, but it sure sounded impressive, especially with Lynch’s loud, aggressive marketing style. 

Autonomy's Meaning-Based Computing marchitecture

And the investors were eating it up.

What really stung wasn’t so much the competition from Autonomy in deals but the stock price. During the Great Recession, when stocks of companies like EMC, IBM, Microsoft, and OpenText were struggling, Autonomy’s stock was soaring. At its peak, it traded at £30, which was 100 times its IPO price. Not bad for a company with products that were essentially a patched-together suite of acquired technologies, just like what EMC, IBM, and OpenText were offering at the time.

Fast forward to August 2011, when HP announced it was acquiring Autonomy at a staggering 80% premium over the previous day's stock price. The total deal came to a massive $11.7 billion, making it one of the biggest B2B software acquisitions at the time. Dr. Mike Lynch, often called the UK's Bill Gates, left the company less than a year later, pocketing around $800 million for himself. He then did what many do after a big payday: bought expensive toys, acquired a countryside manor, started a VC firm, and even received an OBE from the Queen.

This is where the fairytale ends.

The bad news started rolling in just before Mike Lynch was let go from HP, following a disappointing quarter. Then-CEO Meg Whitman (remember her?) didn’t hold back about her dissatisfaction with Autonomy’s performance under HP’s umbrella. By November 2012, HP dropped the bombshell that it was writing off $8.8 billion from the Autonomy acquisition, citing "serious accounting improprieties" and "outright misrepresentations."

What followed was pretty much expected: the SEC, FBI, and the UK Serious Fraud Office launched investigations, and lawsuits were soon filed. This kicked off a decade-long legal battle between HP, its shareholders, and Autonomy’s management, who consistently denied any wrongdoing.

Meanwhile, HP faced its own challenges, and with Meg Whitman out, it began selling off assets. By 2016, my by-then former employer OpenText had acquired Interwoven's assets from HP/Autonomy, and HP eventually sold the rest of Autonomy to the British company Trend Micro in 2017. 

Speaking of fate, this is where the crazy, unbelievable stuff starts unfolding. 

In 2018, former Autonomy CFO Sushovan Hussain was indicted, tried, and convicted of accounting fraud in the US. On his way to jail, he provided evidence against his former boss, Mike Lynch. This led to Lynch being charged with fraud. Despite denying any wrongdoing, Lynch was found guilty in a UK civil court of artificially inflating Autonomy’s financial results during a trial brought by HP. Note the word “guilty”.

After a lengthy legal battle, Mike Lynch was eventually extradited to the U.S. in May 2023 and went to trial in March 2024 on 16 counts of wire fraud, securities fraud, and conspiracy. His co-defendant, Stephen Chamberlain, former vice president of finance at Autonomy, was also on trial with Lynch. Despite being given less than a 1% chance of winning, Lynch pleaded "not guilty." In a surprising turn, the jury acquitted both Lynch and Chamberlain in June 2024, marking a victory for Lynch and his legal saga. While he was still facing civil lawsuits and many more legal bills, this was a major legal victory for Lynch and his team and they decided to celebrate by cruising the Mediterranean on Lynch's super yacht.

What happened next was some unbelievable coincidences.

On August 17, 2024, Stephen Chamberlain was tragically struck by a car in the UK and died. Just two days later, on August 19, 2024, the luxury yacht *Bayesian* was hit by a freak waterspout while anchored near Porticello in Sicily. The yacht sank in a few minutes, and six people lost their lives, including Mike Lynch, his lawyer Chris Morvillo, and Jonathan Bloomer, the chairman of Morgan Stanley International. Interestingly, Bloomer was the chair of the audit committee on Autonomy's board at the time of its sale to HP.

So, within two days, Autonomy’s CEO, his defense lawyer, the company’s VP of Finance, and the chair of Autonomy’s audit committee all died under unnatural circumstances. Coincidence? That’s hard to believe! 

So, what exactly happened to Bayesian?

One possibility is that this was truly a freak accident caused by a rare weather phenomenon. The leading theory is that a waterspout—a type of tornado that forms over water—might have been responsible. But have you ever actually heard of a waterspout? They’re rare and typically not strong enough to pose a threat to large vessels. And a waterspout powerful enough to sink a yacht of that size, while other nearby yachts were untouched? Hard to believe. With no evidence left behind since it occurred on water, the only proof is a yacht at the bottom of the sea.

But Bayesian wasn’t just any yacht. At 184 feet (56 meters) long, it was one of the largest sailing sloops in the world—a sloop being a single-masted sailboat. Its 246-foot (75-meter) mast was the second tallest in the world, and the yacht was valued at around $40 million. This boat was said to be unsinkable, with multiple compartments and all the safety bells and whistles a billionaire would want. Of course, whenever someone says "unsinkable," everyone immediately thinks of the Titanic. Still, if I were a billionaire, I'd want a yacht like Bayesian.

I won’t dive into all the details, but there’s a lot of speculation out there. How could a yacht of this size sink so quickly? And why did six passengers perish while most of the crew was rescued? As a sailor, I’ve followed these discussions closely, and there seem to be more questions than answers—along with an unsettling number of coincidences. If you’re interested, one of the most succinct analyses of the accident is in this video (yeah, the speaker isn't very dynamic but he presents the facts without a bunch of fluff which is what all the media outlets do).

Maybe this was just a tragic, freak accident, but there seem to be way too many coincidences. Of course, there will be an official inquiry because, as far as I know, Italian law tends to find someone to blame when a person dies an unnatural death. So, we are already hearing talk of manslaughter charges, with everyone from the captain and the crew to the yacht builder, and even the weatherman, being accused. But most of that is just for show and for the insurance companies trying to limit the massive payout. Shocking, right?

Hopefully, we’ll eventually learn what really happened. Either way, the story of Mike Lynch and Autonomy is one for the ages, ending in a tragic twist. 

Or is there perhaps another explanation for what happened? 

Vectors of Growth

Every technology company wants to grow. At least, every US technology company wants to grow and companies with VC or PE money behind them must grow. The popular metric of SaaS company performance is the Rule of 40, which combines revenue growth with profit margin. While there has been a lot of focus on profitability in the last couple of years, growing the top line offers a much bigger lever than cutting costs. Growth is essential.

But where does growth come from?

The common wisdom is that to grow your revenue, you need to sell more deals, but there are many ways to skin that cat. I like to use the term "vectors of growth" because they offer companies different directions to pursue. While these vectors are not mutually exclusive, they each come with a cost, and every company needs to carefully prioritize the ones it wants to pursue. Trying to focus on everything means there is no focus at all.

Let’s examine the different strategies to achieve topline growth:

Growth from New Customers

When you want to grow from new customers, the key question to answer is where to find them, which vector to pursue. Another important question is how much you need to change your product or your GTM strategy to pursue a particular vector because such changes require money and time to implement.

- New Geographies

This is often one of the easier growth vectors to unlock. If a company is currently selling in the US, expanding to countries like the UK, Canada, and Australia is relatively simple. Still, it requires that the product works in those countries. Selling a collaboration product like Slack or Zoom solves a universal problem with minimal product changes. On the other hand, HR and payroll products like Gusto or Rippling have to support country-specific labor laws to be sellable in any particular country.

The GTM strategy also requires some changes, usually some type of local presence. But if the product works, these are relatively easy to implement.

- New Segments

Going up-market or down-market is one of the most common growth strategies. Many B2B software companies start by selling to small businesses and over time target larger and larger customers. This strategy is not without product challenges, as enterprises require various customizations, integrations, and security features that were previously irrelevant to an SMB product. Conversely, products designed for the enterprise segment are usually very difficult to adapt for the simplicity required in the SMB market.

The GTM changes can also be quite significant. The enterprise sales process using a direct sales force is significantly more complex, long, and expensive compared to selling online to small businesses. That has an impact on all other functions, including Marketing, Legal, Finance, and Services. As Bill Binch describes on his blog, going after the enterprise is a company-wide motion.

Companies that seem to have mastered selling to all segments are those with products that have been designed for use by a single user and offer value that increases with the user count, following the network effect per Metcalfe’s Law. Examples of such B2All companies include Box, Slack, and Zoom. These companies are very good at attracting individual users in an enterprise and then converting them into enterprise licenses.

- New Verticals

When a company adopts a vertical GTM strategy, it quickly learns that different verticals have different requirements based on the specific needs of the business. For example, subscription billing for media companies requires a high volume of very simple invoices compared to B2B SaaS companies with a low volume of highly complex invoices involving many line items, negotiated prices, ramp contracts, etc. Expanding from one vertical use case to another may require significant product investment.

Similarly, a vertical GTM motion requires a depth of vertical expertise that your typical horizontal sales reps might not have and that needs to be addressed by building vertical sales teams or adding overlay experts.

- New Markets

This is the most radical vector of growth where the company enters a new market, often through an acquisition. And I am not talking about a small technology acquisition that can be tucked into the existing product. I mean buying a business that adds a new product for a different market. Think Salesforce buying Slack. This is what some companies have to do after they have exhausted all the other vectors of growth (or do you still believe that there was some great product synergy between Salesforce and Slack?).

This vector of growth comes at a relatively high cost in cash or equity. Beyond the acquisition cost, there can be significant engineering costs to integrate the acquired products with the existing ones and GTM costs to enable cross-selling of the acquired products by the existing Sales teams.

Growth from Existing Customers

Now, let’s look at strategies to find growth from existing customers, commonly referred to as expansion:

- Adoption Increase

This is the most obvious and perhaps easiest to implement growth vector of them all. The customers already use the product, and the goal is to make them use it more. Whatever the metric, you want them to adopt more units. If your scaling is by users, you want them to expand the user population. If the metric is usage-based like API calls, gigabytes, or dollars, you want them to increase that usage.

This is part Customer Success and part Sales. Customer Success should monitor current adoption metrics and step in when customers don’t utilize what they are already paying for. Maxing out adoption is a great step towards revenue growth while customers who are not using what they pay for are in danger of downsizing or churning, which is the archenemy of growth.

The Sales strategies usually involve sales plays, such as expanding from Sales to Services teams, just like Salesforce has done with CRM. The appeal of this strategy is the relatively low cost. The product usually doesn’t need to be changed and the changes to the GTM motion are relatively low, mostly related to enablement (training).

- Add-On Products

Add-on products are a great way to generate growth from existing customers. The demand typically comes from the existing customers themselves. Eventually, the product is built, and the decision is made to charge for it (as opposed to including it as a feature in the existing product).

The product-related cost is obvious – the add-on has to be built and that has to be prioritized over other product requirements. The GTM cost is relatively low because sales reps have been already asking for the product (because their customers have been asking for it). Sure, there will be some enablement costs involved and some complexities related to pricing, order processing, revenue recognition, etc. But overall, this is a dependable way to add growth from existing customers.

The only caveat is that it must be an add-on – something that adds value to existing deployments. This is not to be confused with the New Markets strategy, where the company builds (or acquires) a new product that has to be sold again, even to existing customers.

- Use Case Expansion

The use case expansion strategy assumes the adoption of the product by a different part of the company, usually a different business unit with a different use case. That often introduces new product requirements because the new business unit has different needs. A good example is OpenAI, which uses its LLM engine for an end-user-facing application (ChatGPT) but also for use by developers who can access it via an API. Adapting a product to support such different use cases requires development effort.

The GTM motion also comes at a tangible cost with this strategy. It likely requires a different sales team with different expertise to pursue the new use case. It may also require different pricing and packaging. This effort is similar to expanding to a new vertical when pursuing new logos.

Growth Strategies for Both New and Existing Customers

- Pricing Optimization

This strategy looks at how to extract more money out of existing or new customers with minimal product and GTM changes while keeping an eye on churn and win rates. It doesn’t always mean just simple price increases; more sophisticated approaches involve pricing model engineering. An example could be the introduction of a usage-based price component while lowering the recurring fees. Another example might be the addition of advertising-supported revenue to paying subscribers, as done by Hulu, Prime, and HBO recently. 

- GTM Effectiveness

This is the mother of all growth strategies because it aims to improve the effectiveness of the existing GTM motion. It can include areas such as pipeline conversion, account allocation, quotas and incentive strategies, win rate improvements, etc. It applies to both new and existing customers and is the entire reason why companies have Sales Operations, Enablement, and Marketing Operations functions.

Summary

There are many vectors of growth available to most companies. Given specific circumstances, some of them are more effective than others. Companies have to choose strategically to achieve the desired outcomes. But choose they must. The worst mistake they could make is to put a half-hearted effort behind all these strategies at the same time. The result is confusion, over-extended resources, and little growth as a result.

Product or Feature?

There is a famous story about Steve Jobs meeting with the founders of Dropbox, Drew Houston and Arash Ferdowsi, back in 2009. At least I think it’s a famous story - it was written up in Forbes after all! Apparently, when Mr. Jobs’ pitch to acquire the then fledgling company failed, he told them: “you are a feature, not a product”. What did he mean by that, and why should it matter?

The idea of what Mr. Jobs was trying to convey is that some companies build solutions that solve a specific problem (or several problems), while others build technologies that make other solutions better. To solve a business problem, you need to offer a whole product. The concept of a whole product has been around since the 1980s, and it means that it provides everything you need to solve a problem. Not every technology that gets sold is a whole product.

Take DocuSign as an example. The flagship product handles e-signatures and DocuSign built a $2.8 billion empire with a $12 billion market cap. But nobody has an e-signatures problem. Electronic signing is but a small part of most agreements, whether those are job offers, mortgages, non-disclosure agreements, and myriad other types of agreements. Each agreement type represents a business problem, and e-signatures are a feature in the solution addressing the problem. A very useful feature, but a feature nevertheless!

Docusign (apparently that's the new way of writing it) was a typical feature company until it eventually expanded into contracts management by acquiring Seal Software in 2020. The recent announcement of the Intelligent Agreement Management platform and the just announced acquisition of the workflow platform Lexion are logical steps towards becoming a whole product.

Speaking of workflow, there has been a debate going on for two decades about the differences between workflow and business process automation (BPA, aka BPM, aka DPA) . The short answer is that workflow is a feature, always embedded within a business application, while BPA is a whole product, usually used to orchestrate processes across applications.

Machine learning too is a feature, delivering value while embedded into business applications to do things such as estimate travel time, recommend spare parts to bring to a repair job, detect fraudulent transactions, or alert drivers to put down their phone. Artificial intelligence, on the other hand, could become a product, especially once someone builds an AI like C-3PO, J.A.R.V.I.S., or HAL9000.

However, there are some software solutions that can be either a feature or a product. Examples include office suites (i.e., Microsoft Office 365, Google Workplace), collaboration tools (Salesforce Slack, Microsoft Teams, Zoom), and file sharing (Dropbox, Microsoft OneDrive, Google Drive). These solutions can be a product when they are used to solve the employee productivity problem, but they are a feature when they are used to solve a problem that requires integration with other applications (i.e., Zoom integrated with a Call Center application). The first thing that Salesforce has done with Slack after acquiring the company was to embed it into existing Salesforce applications – treating it as a feature.

Generative AI too can be either a product or a feature. It can be used as a productivity solution (i.e., for research, copywriting, or translations), or as part of another application (i.e., contract management, search engine marketing, or…gasp…a customer service chatbot). OpenAI recognizes that and packages the technology either as ChatGPT, which is the product sold to users and priced by user seat. But the OpenAI technology is also available as an embeddable engine with an API. That’s the same technology but packaged as a feature and priced for ISVs by counting usage.

Does it matter if software is a product or a feature?

It matters quite a bit for the go-to-market strategy (GTM). Selling a product that addresses specific business problems requires the value proposition for the target buyer in the target market. Such products are typically sold to business buyers, and successful GTM strategy must understand who they are and what problems they have. BTW, the business buyer for employee productivity is usually in the IT department.

Selling a feature requires a different GTM strategy. A feature is part of somebody else’s whole product and its addressable market. It requires playing by the rules of that market, following the solution vendor’s GTM strategy, augmenting its value proposition, going after its target buyers, and making sure that the feature delivers value no matter what moves the vendor makes. For example, if you build a e-forms solution for Sales Cloud, and Salesforce decides to shift its strategy from Manufacturing to Financial Services, you will be figuring out the forms use cases for Financial Services. The same is true for Zoom integration with Marketo and Dropbox integration with HubSpot.

Coming back to Dropbox after examining the feature vs product dilemma, is Dropbox a feature? Yes, Dropbox is a feature that is often used in integration with applications from Adobe, Autodesk, Canva, and Zoho. But like some of the other horizontal end-user applications, Dropbox can also act as a solution for the productivity business problem.

So, Mr. Jobs was only partially right. There, I said it.

Competitive Intelligence Is Not About The Checkmarks

"We need to know what we can do that they can't." If I had a penny for every time a sales rep asked me this question! Indeed, most competitive intelligence work seems to be spent producing a matrix with checkmarks that might look like this:

Oracle loves doing this!

Of course, this kind of comparison is completely useless. It lacks the credibility to be taken seriously by a prospect, it doesn’t have the details to be useful for product decisions, and it doesn’t help sellers win any deals. What does it mean "Limited Solution"? 

Adding rows to the matrix might add granularity but doesn’t alleviate these issues. Just look at this comparison with Box that I found on Dropbox’s website: 

Wow, look, no passwords in Box!

Such a comparison becomes only slightly more credible when conducted by an independent analyst firm, but even then, it lacks the necessary insights. I appreciate that Forrester includes some weighting for each area of functionality in its Wave but scoring 3.00 points for Customers and Accounts doesn’t really tell me much about a Billing product. The Wave may help you get on the shortlist, but it will not win any deals.

So, what should Competitive Intelligence be doing if not comparing features?

The objective of the function is to increase the win rate. That’s it. Increasing the win rate will, at some point, involve enabling the sellers with insights and tools because that’s where the rubber meets the road. However, the Competitive Intelligence (CI) function can influence the go-to-market (GTM) strategy in ways that ensure the sellers work on opportunities they stand a chance of winning.

Rather than thinking of CI output as sales tools, it needs to inform the GTM strategy. That starts with understanding where your competitors are successful. Which market segments do they target, and where are they winning business? The competitor’s website usually mentions several target verticals, but only some of those segments are where they get most of their business, while others are aspirational.

CI needs to find out the competitor’s strongholds – for example, by profiling all their customer references. Yes, this is a lot of work, but it gives you much better insights than the “Industries” tab on the website. Usually, segmentation has more granularity than just industries, which needs to be analyzed. Understanding competitors' segmentation should inform your own segmentation strategy. It may be wise to avoid direct confrontation on your competitor’s home turf, and you may find more success in another segment.

Once you have decided on your target segment, you need to recommend the sales play. Who’s the buyer? Do you start with a single department, or do you go after the entire enterprise through IT? Do you lead with a particular product or capability, or do you lead with a comprehensive solution? Again, knowing how your competitor goes to market can help you make the right decision that will lead to an increased win rate. The CI team needs to find that out and document it - and that is a lot of work as well.

After you determine your target segment and sales play, you need to figure out what’s the best way of finding the targets. CI can yet again contribute by analyzing how the competitors go about it and recommending whether to use the same marketing tactics and communication channels. For example, if you see your competitor doing a lot of work with industry analysts and you don’t talk to any of them, you should probably invest in your own analyst relations function.

Eventually, you need to decide on your messaging. Is it about saving costs, increasing employee productivity, or improving safety? Competitive differentiation is a key element of not just your corporate and product messaging but also your strategy. Understanding your competitor’s messaging - and strategy - can greatly improve the effectiveness of yours.

Ultimately, you do need to train the sellers. But they need to be trained on the target segments, sales plays, strategy, and messaging, which includes your competitive strengths. They may need a tool that helps them learn all of that, including the strengths and weaknesses of your competitors. That tool is not a list of features with green checkmarks in the column under your company's name.

Competitive Intelligence is much more strategic than creating a feature comparison.