By Adam Liska, Airspeed co-founder and CEO
Customer centricity is the thing every business says it wants. Understanding what your customers actually need sits at the core of a healthy company. The hard part is capturing their authentic voice out of a flood of data.
It goes well past good customer service. Customer centricity means putting the customer at the center of your decisions, products, and services, and truly understanding their needs, preferences, and pain points.
The “voice of the customer” is the collective opinion, feedback, and desire of your customers, and it tells you where to point the business next. When customers feel heard, they come back and bring others. Retention and loyalty often decide whether a company grows or stalls.
Sales teams have always been the ones capturing that feedback. Before the internet, a customer walked into a store and the salesperson read their needs on the spot: what they were after, why they came in, what would close the sale. That human read built personalization into the sale.
Then the internet rewired everything. It brought targeted advertising based on behavior and preferences, a real step forward. But one thing stayed missing: the ability to capture and analyze conversational data, where the most honest customer feedback lives.
Conversational data (phone calls, emails, chats, social conversations) is unfiltered feedback. It carries customers’ pain points, objections, desires, and expectations. And it usually stays locked away, out of reach of the sales leaders and decision-makers who need it most.
In sales, everything else is customized. CRM systems run on custom fields. RevOps teams work vast datasets in BI tools like Tableau. Intent data gets captured by segment and target group, and outreach has to be hyper-customized to land. Conversational data is the exception. It often gets pushed through generic, one-size-fits-all frameworks that ignore how your company actually sells, tools like Gong and Chorus.
That gap between customized sales processes and generic conversation analysis costs you insight. It means missed chances to refine your strategy, tailor your product, and win deals. Without a clear read on what customers say in their own words, you are guessing, and you make calls that drift from what they actually want.
Now it is changing. AI bridges customer centricity and data analysis. AI-driven tools analyze conversations, surface tailored insights, customize them to the individual company, and hand you something you can act on.
Customized for the individual company
AI fits the specific needs and processes of your company. It reads conversational data against your objectives, so the insights are relevant and ready to use. You don’t drown in generic information; you get precise recommendations.
The range of what it surfaces is wide. It identifies the objections customers raise on sales calls, so reps can address them head-on and close more. It flags recurring pain points, so product teams prioritize the features that match real customer need.
It also reads sentiment, gauging satisfaction and pointing to where things need work. That steers both support and product, keeping the company aligned with what customers expect.
AI is the missing piece for turning customer feedback into action. The teams that embrace customer-centric AI will understand their customers better than the ones that don’t.
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