The Assumptions Sinking Go-to-Market Strategies

Assumptions are the Achilles’ heel in any go-to-market plan; they’re pervasive and often undetectable until plans are well underway. 

We’ve all heard and relied on a few tried-and-true pieces of advice: follow the data, know the customer, use key metrics to guide your strategies. The problem is – as organizations grow and objectives become splintered across teams, everyone’s interpretation of these things starts to differ. The silent killer in a GTM strategy? Assuming something unspoken is “common sense.” 

Recently, I was part of a discussion hosted by Dan McGaw, where myself and other Marketing and RevOps leaders dissected the assumptions that so often sink strategies. I’ve distilled a few key takeaways below, and highly recommend you listen to the full conversation if you can. 

1. You don’t know what data to prioritize

We’ve fallen into the mindset of, the more data, the better. 

It’s not without good reason: data has been coined the “new oil” of the digital age, particularly given the recent ascent of artificial intelligence, which relies on data to function. Yet, there’s a misconception that collecting data indiscriminately will put you in the lead – and that’s not the case. 

Nina Wooten, Vice President of Revenue Operations at Siteimprove, put it this way: often, companies aren’t starting with the question of what data do we need to collect? Or what information do we need to fill out our customer profiles? Instead, they’re going about things backwards: collecting data indiscriminately and then trying to find the connecting threads. In her words, “Not all data is created equal, and you can’t have everything everywhere.”

Is having tons of data useful? Sure, if you can identify the patterns within it – and that depends on asking the right questions. That’s why it’s fundamental to begin with a data dictionary that dictates what data you're collecting and why you need it. 

This should be a dynamic document that evolves alongside the business, helping to keep internal alignment between teams. It also has the added benefit of avoiding tech sprawl. When you’re clear on what data you need to collect, and why it matters, you’re better able to pinpoint the tools and systems that’ll help with the task. 

Kayvan Dastgheib-Beheshti, Global Head of Revenue Operations & Enablement at Tegus,  shared his thoughts, “Between internal data, product data, and the signals we're getting from third-party vendors, it becomes very difficult to string it all together and have a unifying backbone across the entire data environment. I'm always looking for the “Rosetta Stone” to translate data between different systems and stacks, and have a centralized source of truth. Because at the end of the day, if all of our different teams are generating and creating our own data and aren’t able to share it bi-directionally, we're all speaking a different language, which means our strategies are going to fall apart.” 

(At Twilio Segment, we’ve written extensively about how to put together a comprehensive data tracking plan and how to determine the right data to collect.) 

Along with internal strategies falling out of sync, you’re also risking privacy compliance when there’s no guardrails around data collection. The GDPR stipulates that organizations can only collect and use customer data that’s necessary for their business. And while the GDPR applies to the European Union, international organizations must also comply if they have operations inside the EU. The fact of the matter is, the GDPR set a global precedent when it comes to consumer privacy, and it’s often seen as the gold standard. Several states in the U.S. have already passed their own privacy legislations, and consumers are largely invested in how their personal data is being protected.  

In this regard, data minimization is more than just a best practice; it’s both a legal requirement and a forward-thinking strategy. 

2. You don’t actually know the customer

Know the customer; the mantra of any good marketer. But do you actually know who the customer is and what drives them…or just think you do? 

We’re able to glean so much insight from how a person interacts with our business, and contextualize this data even further with demographic information like their job title or the region they live in. But qualitative data, collected from actual conversations with customers, is also crucial to better understand their perspective.

Kayvan put it this way, “The data you think is valuable probably isn’t, especially when we think about product features and engagement. We like to think we know what in our product is sticky, so we come up with varied proxies, like the number of logins or if someone used the search function. Before we even talk to our customers, we’re running a predictive modeling exercise to see that if someone logs in less than 10 times in a 30-day rolling period, they’re more likely to churn. Well, yeah. But it’s not because you need to send a reminder email. It’s because something in the platform didn’t materialize as they dream that you sold them.” 

Here’s an example from my own experience. I live in the UK, and when I’m filling out a form on a website and I’m asked where I live, I’m usually given several options. Technically, they all could be correct, but should I select Great Britain or England? On the one hand, this is a data problem – it goes back to having that dictionary mentioned above, which should dictate how you’ll organize and transform data to ensure its consistent. But it’s also a perspective problem: not understanding how this could be confusing and frustrating on the customer end. 

As Dan McGaw noted, you don’t want to be in a situation where a customer needs to provide their information – essential, zero-party data – and they’re unable to do so. That’s bad strategizing, which brings us to our next point…

3. Technology doesn’t equal strategy

Tech stacks get crowded quickly. Every team has their own tools that are instrumental to their daily work. Yet as Kayvan pointed out, it’s a trap to think a tool alone will be the solution to your problems. That’s only partially true. It’s how that tool is implemented and used that will determine your success. 

Technology should be a conduit for your strategy. 

This all goes back to laying the right foundation. As Nina said, “It comes down to your ICP [Ideal Customer Profile]. Who is your customer, and why are they your customer? What keeps them coming back? The number of conversations I’ve opened asking this – you get as many answers as there are people in the room.” 

You need to define the countries you’re selling into, what verticals, and who your target audience is. As always, this will evolve, but there needs to be a North Star metric everyone is marching toward. 

Take progressive profiling. This was a tactic that we all endorsed: gradually collecting customer data as you build out the relationship. This data has the ability to transform customer experiences for the better, if it’s used strategically. 

Let’s use the example of someone onboarding with your product. You can build entire email and push notification sequences to help usher customers through important milestones – automating these communications so they’re scaleable. Though what if someone races through the first three milestones faster than usual? Should they still get the automated emails in their predetermined cadence, reminding them to complete those steps? Probably not. It’s noisy and creates a disconnect. Instead, you should evaluate this real-time behavioral data and dynamically update the messages they’ll receive to match. This is where technology meets strategy. 

If you noticed, the second option is also customer centric. In the first setup, technology was being used to make something easier for the company, which is part of the goal. But you also need to be thinking, how can this technology enable a more seamless customer experience?  

Wrapping up

As you can see, all these aforementioned assumptions are linked, and often rooted in skipping over fundamental questions: what data should be prioritized, who the target audience is, how you’re providing value to the customer. Being clear on what metrics everyone should be focusing on (and who’s accountable for what) will forever be crucial when creating a strategy. 

It’s also worth mentioning that the takeaways listed here only skim the surface of what was shared during the webinar. You can watch the entire recording here, and a huge thank you to Nina Wooten, Kayvan Dastgheib-Beheshti, and Dan McGaw for their sharp observations and insight.