Build, Buy or AI?

For a very long time the notion of "build versus buy" was a constant theme in conversations about enterprise growth. Was it better to build a new factory or buy an existing factory? Was it better to build an office park or buy one? The scenarios are a mile long. And there is no perfect answer. The right decision is only really visible in the rear view mirror. But the dilemma keeps a lot of financial analysts busy day and night. 

That brings me to a new construct I am calling "build, buy or AI." It seems to me the world of SaaS software – SMB SaaS software to be more specific – may be shifting. According to a projection in Fortune Business Insights, the global SaaS market will grow from $273.6 billion last year to around $317.6 billion by the end of 2024, with significant further growth expected in the future. Let's run with these numbers for a minute.

AI Slowing SaaS Revenue Growth?

Most of these forecasts are generated by adding up the top-line revenue of the companies operating in the market. So in this case, we can infer, global SaaS users are spending more than $300 billion annually. The percentage being spent by local/small and medium sized businesses is harder to pinpoint. If it's around 50%, which would approximate the percentage of GDP driven by local-SMBs, that would amount to some $150 billion being captured by SaaS software companies from local business owners. That is a very sizable market. A major question is how the SMB snd franchise-facing SaaS vendors will be impacted by AI.

While that remains to be seen, there is perhaps something we can learn from the enterprise sector. As noted in a recent Pitchbook blog post, AI may be putting pressure on SaaS revenue growth, as corporate budgets shift money to AI. The article points out that growth among newly public SaaS companies fell considerably in 2022, from somewhere around 73% YoY in Q1 of 2022 to 32% in Q1 of 24, a more than 55% decline. The fact that the value of Salesforce dropped almost 20% on May 30, 2024, due to weak Q1 revenue numbers, is another piece evidence. Of course macroeconomic issues may also be a factor. Yet weakening enterprise SaaS growth could be an early warning sign for vendors catering to small business and local franchisees. They may need to be prepared for lower-than-expected growth going forward.

Emerging Local Owner Options

Now let's get a bit more specific and play out a simple hypothetical to illustrate a potential new scenario in the SMB/local SaaS sector.

Put yourself in the position of a business owner. Say you want to promote a holiday special: 30% off rain-gutter cleaning. If you have customer names and addresses you could print up a direct mail piece and send it through the US mail. If you have email addresses, you could push an email coupon. And if you have customers' mobile phone numbers (and their permission) you could text them too.

Depending on the sophistication of the business, customer histories and contact details might be kept on paper, in a spreadsheet, or in a CRM database. The latter two will have columns indicating customer transaction dates. If your customer data is digital, you're likely to have customer email addresses. And if you only want your email to go to people who’ve not transacted in the last 12 months, you have a few options. You could outsource the entire process to a consultant or agency or you could use an email marketing or CRM tool – or you could potentially use an AI platform like ChatGPT.

Different Scenarios and Cost Implications

These different scenarios have very different cost implications. In the case of the consultant or agency, you’ll pay a fee to execute the campaign. If you're using an email marketing application or CRM solution, you're paying a monthly subscription and you might still need outside expertise. In the AI scenario, you would upload information about your business and the spreadsheet into ChatGPT or Claude and prompt it to "generate a promotional email that offers customers who have not transacted in the last 12 months a 30% discount on all gutter cleaning and then email that offer next Tuesday morning at 6 am PT."

This assumes the AI tool that can seamlessly connect your customer database with an email client. Presumably, if you’re a Microsoft 365 or Google Workspace user, this will become a relatively simple process – dare I say a breeze.

If this type of operation becomes an actual breeze for the business owner, then the implications for SaaS providers and digital agencies are considerable. This AI option potentially gives the business leverage to negotiate better terms with either their agency or, maybe, the CRM provider. And if the AI tool is $20 a month (e.g., Gemini, ChatGPT), that will put significant price pressure on legacy vendors and providers.

This is just a simple hypothetical. But it does offer a window into how local businesses might start to think about their options, as AI tools advance. What’s to stop a local business owner from turning to AI for any number of marketing and adjacent functions that today are fulfilled by an outside agency, consultant or by an internal employee using SaaS tools. And there's a wave of next-generation tools coming, which incorporate AI at the product's core. They aspire to be more capable, easier to use and cheaper than legacy solutions. See, for example, CRM: Hubspot vs. Day.ai.

Barrier: SaaS User Inertia

As we continue to observe, investigate and consider the implications of AI in local, it’s worth understanding that the biggest barrier for local business adoption of new AI tools* is familiarity/comfort/complacency/inertia – aka if it ain’t broken, don’t fix it. Once people are invested and comfortable with something, including and perhaps especially software, there will be resistance to learning a new system – even if it's cheaper and purportedly easier to use.

We've directly and vicariously seen this play out in various small and large business contexts. But while the power of familiarity and inertia are great, relying on them as a retention strategy is risky. To hold onto the customer, the digital agency may need to deliver more service and value. The SaaS provider, already building AI layers into their solutions, will have to really deliver and make the product easier to use and more intuitive. But if the AI layer is just performative or for PR purposes that will be quickly revealed.

The Way Forward

All of this so far is really just a thought experiment. The real world is obviously complex and fast-changing with lots of moving parts where local meets AI. Where and how all these elements will coalesce or collide is still unclear.

That's precisely why we created Dialog, to bring thoughtful discussion, original data and meaningful insights together to help clarify these murky waters. This is and will continue to be dynamic process and, in our approach, a collaboration with our members.

Nothing will be entirely clarified or resolved overnight but we're committed to engaging and sharing our perspectives, to help our members stay ahead of any disruption and gain a strategic edge.

*Most existing SaaS companies are rolling out AI capabilities. In our SMB survey earlier this year ~57% said at least some of their existing SaaS tools had incorporated AI.