VeraData’s Roughly 900 Engagements Show Why Targeting Beats Volume

By Amara Osei

After nearly 20 years and roughly 900 client engagements, the founder of VeraData says customer acquisition is a targeting problem, not a volume problem. The founder’s framework starts with a distinction owners miss: reach and retention depend on different customer signals.

What did VeraData’s first client reveal?

VeraData’s founder started the company in 2007, expecting that a genuinely useful product would attract the right people. “I was wrong about how they’d find it,” the founder said.

The first client was a nonprofit organization trying to grow its donor base. It used broad outreach, general messaging and high volume, assuming a wider net would produce enough donors. It reached plenty of people, but almost none stayed.

Across that first engagement and roughly 900 organizations served since, the founder concluded that the product was not the problem. The gap was a precise, data-backed picture of the individual most likely to engage, return and bring others with them.

Why do broad acquisition campaigns underperform?

Most entrepreneurs, according to the founder, treat acquisition as a volume problem: reach more people and close a higher percentage. The founder says the difference between good prospecting and broad outreach is not a few conversion percentage points. In many cases, it separates a business that compounds from one that churns.

When VeraData modeled a client’s customer file, it did not simply ask who had bought once. It assessed which individuals were statistically most likely, based on behavior, demographics and history, to take three distinct paths:

• Make a first purchase.
• Buy again.
• Become a high-value long-term customer.

The founder says each outcome requires a different model because its predictive signals differ. A first-time buyer, repeat buyer and highest-value customer are not the same person, and treating them as one audience ranks among the most expensive mistakes a growing company can make.

When should data become a prospecting tool?

The work changed when the founder stopped treating data only as a reporting tool. VeraData began building models that identified people most likely to buy before they raised their hand, shifting the exercise from reactive analysis to prediction.

The founder said: “It took me a long time to understand that finding the right customers is not a creative problem. It is a math problem.” Once the model contained the right equation, the founder said, its answer began to repeat.

Which customers should founders study first?

In the founder’s method, the practical starting point is the best existing customers, not the most recent ones. Those are the customers who returned, spent more time with the business and sent others its way.

The founder says the useful pattern extends beyond demographics. Owners should compare behavior, timing, how each customer first found the company and what they engaged with before buying. Even a pattern visible at small scale can begin a real targeting model, although most businesses already hold more signal than they have organized for action.

Where does broad reach waste money?

Another recurring mistake is what the founder calls “premature broad reach.” Pressure to grow quickly, especially early, pushes organizations to contact as many potential customers as possible. Untargeted outreach burns acquisition budget on people unlikely to stay, while delivering the vanity metric of volume and missing retention’s compounding effect.

Organizations that outperform, according to the founder, are not those conducting the biggest outreach. They identify exactly whom they want before spending a dollar, using known customer information to sharpen where they look next.

Can a small business use this approach?

The founder says the problem is not reserved for large companies with data science teams. Organizations of every size can treat customer knowledge as a competitive asset rather than a byproduct of sales activity, then apply what they know to the next campaign.

Every campaign, transaction and customer interaction adds a signal that can make the next decision sharper. The founder expects businesses that build this engine early to look different three years from now from organizations still casting wide nets and hoping.

What should change next?

The founder’s practical test for the next acquisition decision is whether customer data makes the next prospect more predictable, rather than merely adding another row to a report. The founder believes the required data is usually closer than business owners think, but it creates an advantage only when they decide to use it.