Taking a new product or service to market can sometimes feel like a stab in the dark. With all the variables to consider — human behavior, rapidly shifting markets, aggressive competition — it can become a real challenge to formulate your go-to-market strategy. That’s why so many companies are turning toward automated sales and marketing tools like HubSpot, Marketo, and Ingram to help execute their go-to-market plans. Tools like plug-and-play components, market analytics algorithms, and consumer database analysis that can automate the sales and marketing stage of the process.
Of course, there’s much more to a real GTM effort. Shaping the value proposition, targeting customer segments and delivery channels, organizing and bundling offerings, defining a pricing and payment model, positioning the brand, and more. While they can be informed by data, these tasks involve ambiguity and are harder to automate — at least today. There’s no telling what artificial intelligence and machine learning may be able to do a decade from now, or next week.
So as we move closer to automated go-to-market strategies, how do we strike a balance between data and human intuition? Let’s consider the advantages each can bring.
Where Data Can Help
Data speaks louder than words. As Steve Jobs famously said, “People don’t know what they want until you show it to them.” And there is some truth to that. When you ask consumers directly, their answers don’t always reflect their actual behavior or desires. But large datasets can reveal larger truths. By analyzing consumer data, you may discover patterns of behavior they can’t see in themselves. You’re able to find solutions to problems they don’t know they have. This can help you position your product in the market where it would be most effective.
We don’t always know best. When executing a go-to-market strategy, we have our own ideas about what should happen. We often believe we know what people want and how they will best receive our product. Or we look to strategies of other companies that may have worked (or failed). Algorithm-driven tools can circumvent our preconceived notions and uncover new opportunities by getting around our bias and cutting right to the heart of what consumers really want.
Where Data Can Hurt
In a saturated market, creativity wins. Countless products and services enter the market every day, and it can be difficult for most consumers to tell the differences among them. A creatively differentiated offering can set you apart from your competitors. But in a world where every company is using the same tools and algorithms, things start to look more and more alike. Yet the human mind is a machine that notices difference. The more differentiated your entry into the market, the more your customers will notice you.
Robots aren’t perfect. We tend to think of algorithms as unbiased machines, free from human error. But it’s easy to overestimate them. Algorithmic tools rely on data sets that may be incomplete or unreliable. Even worse, they are built by humans, and sometimes infected with human bias. But just as we humans generate bias, our built-in BS detectors can spot it. The human tendency to challenge and question everything put in front of us can help us rescue the mission when things are just not adding up.
Humans + machines: the ultimate go-to-market strategy
There is no perfect algorithm to create your go-to-market strategy (yet). But that doesn’t mean data-driven tools can’t be useful. Let the robots do what they do best — crunching reams of data to guide sales and marketing toward the right targets, and automating process flows where humans are hopelessly inefficient. Meanwhile we humans should do what we’re best at — translating complex, dynamic, and ambiguous situations into coherent and creative strategies.
When data and design thinking come together, you can create a go-to-market strategy that doesn’t just respond to what people are asking for. It gives them what they crave.