Identifying the Perfect Prospects

Mar 28, 2022

Have you ever struggled to define the true value that you’re getting from prospect-oriented marketing channels? If you have, you’re in great company. Marketing for new customers is challenging. The more established your business becomes the less low-hanging fruit you have left to pick.

For many this results in dwindling, or even negative, Return on Investment with acquisition efforts.

Most acquisition-style marketing campaigns are still focused on achieving the lowest cost per exposure. Display, mass saturation mail, linear TV, SEO, and PPC are all implemented with CPI (Cost per Impression) in mind.

The historical reason behind this is that these channels were designed to target noncustomers and thus had a much lower response rate than customer marketing initiatives. The approach was to canvas the market with digital or traditional branding exposures to warm noncustomers up to the brand. 20 years ago, in a much less competitive environment, simple billboards or mass mailings with Valpak were the best ways to get an exposure in front of everyone to see who happened to be in market.

More recently, an abundance of consumer data has brought about a much more targeted approach.

It’s now possible to cut through the clutter to identify those most likely to engage with your business BEFORE launching the first campaign. Just like fishing with a fish finder, you can now quantify the opportunity and make more informed decisions before casting your (often expensive) net. The process I will outline below is equivalent to a fish finder. It doesn’t guarantee a catch every time, but you will be sure that you’re casting your net into the right waters.

For businesses that collect and store customer data with NAP (Name, Address, Phone Number) information, the first step is gaining a deeper understanding of who your current customers are. Providing that you’re housing accurate data, you already know how each individual customer behaves, or transacts, with your business. If you also store lead data, you know who showed interest in your business but wasn’t fully sold. A simple Customer Segmentation, which can be done through querying a CSV or Excel file, can set the foundation for understanding the triggers for specific desirable or undesirable transactional behavior.

If you could duplicate a specific segment of your customers, what characteristics would they have?
Similarly, what group of customers would you like to eliminate? Everyone is likely to have slightly different answers as they’re business-specific, however most business owners are likely to have the answer to both questions.
If you’re storing customer transactional data, you have nearly everything you need make those visions a reality. A simple customer segmentation can start out with identifying groups like:

    • Highest Revenue Customer Accounts
    • Buyers of Preferred Products/Services
    • Low Touch/Effort Customer Accounts
    • Customers with Upsell Opportunity

On the other side of the coin, you can segment customer groups like:

    • Low Revenue Customer Accounts
    • Buyers of ONLY Undesirable Products/Services
    • High Touch/Effort Accounts
    • Customers with Capped Revenue Potential

What you’re doing with this analysis is laying the foundation to build upon for prospecting. Again, the more you know about your customers the more informed you will be in your prospecting initiatives.

Think about this scenario. You walk into a networking event full of brand-new faces. Everyone is engaged in conversation and to work the room you must walk up to random people, start a conversation, and gauge their fit as a prospect for your business. First, this is my nightmare. The idea of wasting time, making small talk until you can sprinkle in a few elevator pitches, while likely missing out on at least a portion of the right audience is maddening. I have plenty of ultra-friendly friends that thrive in this environment, but I would still argue that this approach is at best like cutting the lawn with a pair of scissors. I typically end up in a corner scrolling through emails after half an hour of going through the motions. This hypothetical represents blindly engaging in prospecting campaigns based on CPI (Cost per Impression). There’s no guarantee of quality or fit, but if you throw enough stuff against the wall……

Now let’s say you walk into that same room of people, and everyone is wearing HUGE lanyards (not the kind designed to make it difficult to see contact info) with labels showing what they’re interested in discussing. You can walk through the room until you see the appropriate indicators and engage in meaningful conversations. Let’s even say that each interest is color-coded so you can quickly gauge how many people you’d like to talk to and govern your conversations accordingly. This hypothetical represents targeted prospect marketing. Shrinking your audience to the most likely buyers, who are likely to transact with your business in a favorable way, will help eliminate the waste.

Even the friendliest of us would prefer the second scenario.


“You don’t have to be great to start, but you have to start to be great.”

– Zig Ziglar

Once you identify your desirable and undesirable groups of customers through Customer Segmentation, you can then enrich that file with consumer data to learn more about the TYPES of people that transact in those desirable/undesirable ways. Consumer Data Aggregators, a handful of whom are very reputable, compile thousands of data points on individual consumers across the country. They standardize and normalize this data so what they’re left with is a highly actionable file with demographic and psychographic profiles for each consumer.

A data scientist, either in-house or a vendor partner, can then append all this useful data to your customer segments. You then instantly know exponentially more about each of your customers. More importantly, you’re able to recognize similarities within groups, and differences between groups, to help point future prospecting initiatives in the right direction.

The next step is to compare each Customer Segment to an index of the market. You can then study the prevalence and absence of each trait in your Customer Segment compared to the market as a whole. Doing this results in the identification of positive and negative variables.

A positive variable is a variable that is MORE present in your Customer Segment than the market as a whole (represented as a percentage). If you see that 40% of your Customer Segment has a cat, but only 20% of the entire market has a cat, then cat ownership is a positive variable.

A negative variable is a variable that is LESS prevalent in your Customer Segment than the market as a whole. If 40% of your market owns a dog, but only 15% of your Customer Segment does, then dog ownership is a negative variable.

Already, you have actionable insight to assist you in targeting more likely prospects. You can filter the market by requiring positive variables, and eliminating negative variables, to produce a more targeted list.

More importantly, you now have the resources to empower a data scientist to build Predictive Analytics that encompasses all positive and negative variables into a single algorithm. This algorithm will use EVERY statistically relevant variable to assign a Probability Score to each individual prospect. This newly scored file can be simply sorted to help you:

    • Eliminate 20-40% of your market that is unlikely to engage
    • Focus your marketing exposures on the right individuals
    • Dramatically increase your Return on Investment on prospecting campaigns

Once this process is complete, you never have to go back to the “old school” way of building your quilt of independent marketing services. Instead, you are empowered to start with a core of data and understanding that will guide each decision and have all marketing channels working together synergistically.

It’s still very important to ensure that you have a reliable data scientist doing the work. Just like anything else, there is a skill involved in producing effective predictive models. My company, Deliver Media, has produced hundreds of predictive models in a wide variety of industries. Although they are all unique to the individual business, they ALL dramatically elevate response rates. The product of that effort has us using hundreds of business-specific “fish finders” to ensure that our clients are always catching plenty of fish.

Do you still need to invest in content initiatives like SEO and social so prospects can do some research on your business and brand? Of course, you do. That’s like weaving a wider net to cast into the fish-dense waters. It’s part of the foundation to ensure that prospects can find you independently and there’s plenty of relevant info to digest at their own pace. The main difference is what you do next. Instead of scouring websites of hundreds of vendor partners and making cost-based decisions, you can now approach a target-rich audience with multi-channel integrated marketing campaigns.

As Zig Ziglar once said, “You don’t have to be great to start, but you have to start to be great.” If you need a little help taking that first step, the team at Deliver Media is always here to walk you through the process. If you want to take the plunge, Let’s Talk!