Validate target audiences from customer segmentation
Updated: a day ago
Using CDPs as a segmentation engine.
When planning out demand generation strategies, brand awareness and targeted personas are often the very first pieces. Actually, the demand generation doesn't really work at all without customer segments. Congratulations if you're one of the lucky ones who just resonate with who you need. I mentioned in the first part of this series on customer data platform (CDP) fueled demand generation that validating target audiences from customer segmentation is one of the first and most valuable ways to unlock your customer data with a CDP.
Regardless of what line of business you’re in, B2B and B2C alike, your target customers are going to be a diverse mix of people with different needs – and these are going to change as they move along the buying process and approach a purchasing decision. This means each customer segment is going to need its own personalized customer journey.
To deliver messages to each of these prospects, addressing their unique needs at each stage of the sales journey, you need to segment your leads – both at the moment you capture them and on an ongoing basis as their relationship with your brand changes.
With today’s marketing, mass is viewed as inefficient and so out-dated. You should not just aim for every possible lead you can get, either; rather look to get highly-targeted, relevant leads that are likely to go all the way and buy from you. You need to know exactly what makes your target audiences tick, what they’re looking for from your brand, and pinpoint highly specific needs. Without this kind of personal knowledge, your segmented lists are going to be too generic and you’re going to leak desired leads between different stages of your funnel. This is where customer segmentation from CDPs comes in handy for demand generation.
It's important to note here, that there's a big difference between a customer segmentation and a segmented contact list. There's a lot of marketing tactics that segment lists with just a couple to rules to drive workflows. While these tactics may inform some behavioral segments, in the case of utilizing a CDP for customer segmentation, I am talking about defining valued customer segments from insights gained from contextualizing different attributes of your existing audience.
The practice of using a CDP for better customer segmentation is definitely taking hold. In fact, according to a Forrester survey, 34% do expect segmentation to be a key CDP feature.
Slice and Dice N ways
If you ever wondered why VIEWN is a fitting name for a CDP and segmentation engine. Here it is. Segmentation is probably the most valuable byproduct of being able to build customer profiles from data. Once you start building individual profiles, you have a modular organization that allows you to keep building on (adding data sources) while slicing and the dicing the data until you find the “most valued customer segment”. You are given numerous and almost indefinite approaches like trying to use media usage and location to define a segment. Remember though getting to “N” does not mean just pouring things into a data lake. Keeping in mind context and mapping things that make sense is still a prerequisite to getting a favorable outcome. You’ll find in more complex enterprise CDP architectures, profiles are built from data sources AND databases because you just can’t just blindly collect data before using it. Your wheels will turn in the same place for a long time otherwise.
Kinds of segmentation data to use
I'd also like to challenge the misconception that a 360° view of the customer from just a CRM, is NOT enough to give you the segmentation you need for a purchase. A CRM profile is meant to be used for a salesperson in the midst of a conversation or engagement. A CDP profile is meant to be used by marketing and product to understand their customers and to get insights based on them. For insights that will inform demand generation strategy, CRM is just one of the data sources in which to tap.
Given the objective of building CDP profiles to understand valuable segments, let's go into the different examples of segmentation data we could potentially use. Characteristic segments describe key attributes of your target audiences in areas where you need to differentiate. A lot of marketers would like valuable demographic data like gender and age. Search engines and apps have really gone far in leveraging location and keyword data.
Examples of characteristic segments marketers use include:
Geographic: Location, country, language, etc.
Demographic: Age, gender, nationality, etc.
Sociographic: Marital status, children,
Psychographic: Personality traits, values, attitudes, interests, etc.
Behavioral: Clicks, views, responses, keywords, journeys, usage
Professional: Occupation, income, education, etc.
Firmographics: Company size, industry, position at company, etc.
There are a lot of different data sources to enrich your CDP for insights. What you will often find is that your marketing team utilizes a lot of different tools in order to collect these characteristic segment data. For example, a lot of good behavioral data will come from your CRM and marketing automation platforms like SalesForce, Drip, and Mailchimp. Key psychographic, professional, and sociographic data can often be gathered directly from the prospects during the engagement process. VIEWN’s team recommends surveys and lead generation forms as an easy way to get reliable data. I don’t know how you add focus group results to a big data set yet. Your sales representatives can also be tapped as data collectors (into a CRM) with their different conversations. When the budget allows purchasing intent data will give demographic, geographic and even some psychographic data tied to a particular contact or zip code. B2B firmographic services tied to DUNS numbers are also available to the enterprise, in the case where industry and firm matters.
Validate Target Audiences
Since a CDP builds actual profiles of customers that you have. Analyzing the characteristics of these customers profiles, lets you validate that your initial target definition is actually the customers you have. A target or persona is created in the beginning as a starting point. As you get customers you can see how close you were in your assumptions that drive purchasing. Validation needs to happen continuously even as you get your initial customers. Businesses often ask a few questions even at the contract stage. What is great about organically distilled customer segments you not only validate your know audiences, it is possible to uncover underutilized segments as well. Significant ROI can be gained in issuing new customer acquisition campaigns targeting these valued segments because you can still utilize the same marketing stack.
At VIEWN, our hypothesis is that the most valuable segments will be found looking at the characteristic segments of product/media usage, demographic and sociographic profiles, and purchasing attitudes. Now to get to these segments we may have to connect to different sources, but we are methodical about it as to preserve the context and not overwhelm ourselves unnecessarily. Product usage gives you the who?, what?, when?, where?, how? Demographics and attitudinal data gives you the why?, who else?, where else?, and how else?. The answer to each of these gives you a validated target audience and set of valued customer segments. Find better quality clients going forward, keep the ones that make sense.
For some case studies on CDP-dirven customer segmentation see this blog.