For more than 30 years, much of my work has revolved around the same fundamental question: how do you find the customers who genuinely need what you offer?
The methods have changed many times. We have advertised, sent letters, made calls, bought databases, distributed newsletters and run digital campaigns. But the underlying task has remained the same: finding the few relevant customers among all those without a current need.
The ideal I have been working towards is actually quite simple: to spend time and attention only on people and companies for whom our product or knowledge is genuinely relevant.
I believe AI can bring us closer to that goal. Not necessarily by automating even more outreach, but by helping us identify the right few, understand their situation better and have something relevant to contribute before making contact.
When reach was the route to precision
When I began working in marketing, reach was a prerequisite for precision. If you wanted to reach ten decision-makers across a country, you might buy a full-page advertisement in a national newspaper. The advert was shown to hundreds of thousands because that increased the likelihood that the right ten would see it too.
Then came company databases and large lead lists. You could buy 10,000 company records and contact them directly. The method felt more precise, but the underlying principle was unchanged: we approached many people to find the few who might have a current need.
Perhaps we are moving from buying access to 10,000 names towards investigating which five companies we have a genuinely good reason to contact.
What if we started with the five?
Imagine that instead of buying a long lead list, a company asked for five businesses that might have a particularly good reason to be interested in its solution right now.
Not simply five names and telephone numbers, but five reasoned suggestions:
- Why might the company have a current need?
- Which changes or challenges might it be facing?
- Who would be relevant to speak with?
- How does the company describe its own situation?
- What knowledge can we contribute before attempting to sell anything?
This is not yet a machine to which we can uncritically delegate sales work. But it is a direction that is becoming increasingly realistic as AI becomes able to collect, compare and structure publicly available information.
From target group to actual situation
Traditional marketing often works with target groups: industry, size, geography, revenue and job title. These are useful facts, but they do not necessarily tell us whether the need is current.
Two companies in the same industry and of the same size can be in very different situations. One may have just entered a new market, hired new employees or launched a product. The other may have no plans to change.
The interesting question is therefore not only who the company is. It is also what is happening around it right now.
News, job advertisements, professional posts, product launches and market changes can point to a possible issue. Not as proof that the company will buy, but as a reasoned invitation to explore whether we can contribute something relevant.
Research must become useful
Once the five companies have been identified, the real work begins. Knowing whom to contact is not enough. You also need something meaningful to contact them about.
The research may show that several of the companies face variations of the same problem. That provides a basis for an article that tells the story of a recognisable situation, describes the consequences and explores possible solutions.
Only then do we make contact. Not with a generic sales email, but with a relevant observation:
“We have been working on an issue faced by several companies in situations similar to yours. I do not know, of course, whether it is relevant to you as well, but we have collected our observations and possible solutions in this article.”
The article should not be an advertisement disguised as professional content. It should be useful even if the recipient never becomes a customer. Its purpose is to show that we have made the effort to understand the problem before asking for anyone’s time.
One-to-one marketing – at last?
We have been talking about one-to-one marketing for many years. Too often, however, it has meant sending the same standard email to thousands of people with a first name inserted automatically.
That is not personal marketing. It is mass communication with personalised fields.
The more interesting possibility is for research, content and outreach to begin with a specific situation. AI can make some of the preparation economically viable, but human judgement remains essential.
We must decide whether the connection is real. We must formulate the insight that could help the recipient. And we must have enough judgement not to contact anyone when the relevance is unclear.
Precision also requires respect
The more precise the technology becomes, the more important it is to use it responsibly. The objective must not be to monitor individuals or pretend that we know more about a company than we do.
We can work with publicly available professional information and form a hypothesis about a possible need. But we should be open about the uncertainty and allow the recipient to decide whether the issue is actually relevant.
A good approach should therefore be able to withstand a no. It should be specific, respectful and useful without being intrusive.
Fewer approaches with greater value
I do not believe AI’s most important contribution to sales will be enabling us to send even more messages. I hope it will be the opposite.
Five thoughtful approaches can be more valuable than 10,000 automated messages if they are built on genuine relevance and a credible understanding of the recipient’s situation.
The most appealing prospect is therefore not only greater efficiency for the seller. It is a better experience for the recipient. Nobody wants more irrelevant offers. But most people would welcome a good solution to a problem they actually have – especially if it is presented at the right time and in a way that helps them understand the issue better.
After a long working life spent looking for relevant customers, I believe this may be the direction in which we are moving:
Not interrupting thousands in the hope of reaching the few, but understanding the few well enough to contribute something relevant.
It is still a hypothesis. But it is a development I very much want to help explore.
Shall we identify your five?
Waltham helps companies with market insight, customer selection and content based on real business problems. A first experiment can be limited to one issue, five relevant companies and one professional article.