How Financial Services Teams Identify Their Best Prospects

Financial services teams well know the challenges of introducing new technology. There is already so much of the legacy stuff, often woven throughout the many businesses in a network of perilous dependencies. Pull out the much-reviled DOS-based quoting tool and who knows what might happen.

Yet something must change.

Recent history has catapulted your buyers forward seven years, technologically speaking. and firms that sell to them have no choice but to adapt. And yet there is good news: Your firm’s digital transformation need not happen overnight. Nor must it occur evenly.

Any financial services Marketing or Sales team can transform itself into a center of excellence without much budget thanks to an account-based pilot. One of the easiest ways to begin? Identifying your in-market accounts.

Start with a target account scoring model

All the big technological shifts occurring today can be summed up in a word: Visibility. Most of your buyers’ research now occurs online—whether they’re institutional investors or risk officers looking for insurance—before you are ever aware. That means financial firms are better able to peer into their target accounts and identify the companies and individuals most likely to buy than ever before.

In the recent past, the best companies could do was blanket the market in full-bleed print ads. Now, they can pick their targets with precision, based on data and science.

What this means in practical terms is that financial marketers that identify their in-market accounts (ones demonstrating early signs of interest) can focus on just those companies. For example, you might notice that many advisors at a particularly large firm begin downloading your ebook. Based on that insight, you could prioritize that account for more targeted sales outreach. You can, in effect, invest more in the winners and less in the others. (Which can of course change quarter to quarter.).

To know which companies or teams are the winners, however, is the trick. You’ll want to start with a scoring model. Today, there are four broad areas of data you might consider. You may already have some of it (though it may be scattered across systems). With other data, you may have to purchase it. Not all are necessary, but the more the better.

Combined, this data gives you that view of who’s “in-market,” or searching for you. Together, the four data types create the acronym “FIRE”:

• Fit—how well does a firm fit your requirements, and you theirs? (E.g. Are they low-risk?)
• Intent—how actively are they researching products like yours across the internet?
• Relationship—does your team have relationships with key leaders or investors there?
• Engagement—how actively are they visiting your web properties or engaging with your marketing and sales efforts?

The engagement data often comes from your website, CRM, and marketing automation system. The relationship data will come from your sales team (or sometimes, a software like LinkedIn). The fit data will come from a scoring model that you either develop yourself (a fitness rating system of 1-5 stars is enough to begin) or obtain through a platform like Demandbase, which calculates it for you using machine learning. Finally, intent data—the most sought-after of the bunch—is something you purchase from an intent data provider. (Also available through Demandbase.)

Identify what you already have in the way of Fit, Relationship, and Engagement, and then engage with an intent data partner who can help fill out the rest.

Use your intent provider to scan the known universe

In the case of data, “Intent” means “a presumed intent to buy.” It is an indication that prospective clients or decision-makers within companies who might buy have taken actions somewhere online that reveal their intention.

The providers pick up on those far-flung digital activities in a network of data sharing. There are several such groups, Demandbase being one of them. It works like this:

• Buyers conduct research online, on ratings agency sites, lender comparison sites, and publications like The Wall Street Journal and Yahoo!
• Those publications send privacy-safe data to intent data providers.
• Intent data providers use machine learning and artificial intelligence to figure out which visitors work at which firms or companies.
• Buyers of intent data can “enrich” their existing list of accounts with real-time data on which ones are looking for, say, commercial loan products like theirs.
• Buyers of intent data can also combine this with their website Engagement data to “unmask” some anonymous website visitors.

With Intent data, you can pull a list of companies that match your criteria—Fit, Relationship, and Engagement—and are also exhibiting intent to buy—Intent. A bank looking to market particular financial products could use this to shorten their list to just those companies who are both a fit and showing intent, and focus their efforts there.

After this work, the resulting list will be a group of companies that exhibit every indication of both being good buyers (low risk, high-yield) and of being interested in products like yours. It’s a level of insight most financial services sales teams are unaccustomed to, and you can use it to launch an account-based pilot program.

So begins your digital transformation

If pouring more resources into fewer higher-value and interested accounts pays off, it helps you establish your team as a center of excellence. You can help lead your company’s digital transformation (you will have the data to prove it), and adapt to a world where everything about buying and selling has changed.

It doesn’t take the entire business’ approval to start. Just you, a pilot, and data about your buyers’ intent.