Product teams face a never-ending struggle to come up with new features to develop for customers. And no matter how you look at the task, it’s anything but an exact science. In fact, Steve Jobs famously said that “a lot of times, people don’t know what they want until you show it to them.”
But not every product team has (or should have) the kind of blind confidence that Jobs might have had. That’s why it’s so important to take a data-driven approach to product development wherever possible—to mitigate some risk and build a roadmap that aligns with customer wants/needs.
Unfortunately, some of the biggest problems arise when it comes time to prioritize your ideas. There are a variety of product development strategies that can help. And with intent data, you can fuel a product roadmap that’s sure to lead to success.
The Value (and Drawbacks) of the Kano Model
Product managers have always applied models to their decision making that can make feature development as much of a science as possible. You could use the Value Versus Complexity Model, weighted scoring, the buy-a-feature strategy, story mapping, and so many other approaches.
But one that really stands out to us is the Kano Model:
“The Kano Model is an approach to prioritizing features on a product roadmap based on the degree to which they are likely to satisfy customers. Product teams can weigh a high-satisfaction feature against its costs to implement, to determine whether or not adding it to the roadmap is a strategically sound decision.”
At a time when B2B buyers have so many options, this kind of customer-centric approach to product development is almost essential. When customer delight is the North Star, it’s tough to go wrong.
In the Kano Model, your goal is to build a roadmap that ignores features that customers would be indifferent to or dissatisfied with. Instead, you load up on features that bring excitement, performance, or meet basic expectations.
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There’s just one drawback—how do you actually know the amount delight that individual features will bring to customers?
This is the million-dollar question that Steve Jobs might say customers wouldn’t be able to answer anyway. Instead, you need ways to analyze subtle buyer behaviors and decide which features to prioritize (even if customers aren’t explicitly mentioning them. Intent data is the answer to this Kano Model drawback.
Intent Data Makes Product Development More Proactive
When you invest in third-party intent data, you’re getting insights that go beyond how prospects and customers interact with your owned content. You benefit from keyword analysis from billions of daily web interactions that are ultimately mapped to stages of the buyer’s journey in real time.
This kind of real-time data helps you disprove the idea that data-driven product development is reactive. Instead of constantly playing catch-up by developing features that reactive analytics surfaced months ago, intent data provides insight into subtle clues about what’s important to in-market prospects right now and in the coming days/weeks/months. These clues give you the push in the right direction to be more proactive.
Opportunities to generate customer delight will decay over time. And it makes sense—something that’s important to customers today might not be so valuable a few months from now. The closer you can get to the source and roll out features that align with up-to-date customer needs, the easier it will be to delight customers with new product developments.
Without real-time intent data, customer interviews can give you an idea of what features might satisfy customers at the most basic level. But for the “excitement” features that deliver disproportionate levels of delight, you need to go beyond black-and-white product road-mapping that follows customer feedback.
Being able to spot trends in the competitors your customers interact with as well as the content that they spend the most time engaging with during research phases can give you a competitive advantage from a product development perspective.
But whether you’re using the Kano Model or some other product development strategy, the real challenge is finding unique ways to make the most of your data to inform road mapping. This starts with understanding the what, why, and how of intent data.
Do you know which specific companies are currently in-market to buy your product? Wouldn’t it be easier to sell to them if you already knew who they were, what they thought of you, and what they thought of your competitors? Good news – It is now possible to know this, with up to 91% accuracy. Check out Aberdeen’s comprehensive report Demystifying B2B Purchase Intent Data to learn more.