How to build Successful Personalized Marketing Experiences?
As marketing becomes more and more advanced, personalized marketing is critical.
Personalization in marketing is real, needed and possible. It re-enforces your brand, and can mean the difference between being competitive or disappearing into oblivion.
But how do you that ?
In this blog post I want to discuss a methodology and a personalization model that helps you to:
- segment your audience, beyond demographics and geographic
- link your business objectives with 1-1 personalization campaigns
- understand how personalization actually works
Let’s get started!
Why Data Needs Strategy
The big overarching business benefit of personalized marketing experiences is the following:
People tend to respond better and be of greater value to your business when they feel their needs and interests are being specifically addressed in personalized communication.
On a deeper level, the business benefits of personalization are:
- Likelihood of buying: When your marketing messages are relevant to the situation of customers and their interests, they are more likely to buy.
- Increasing customer lifetime value: Focusing on increasing the lifetime value of each customer as much as possible by making your marketing contextual is a key driver of long-term profitability.
- Better insight into customer base: Examining the performance of certain customer segments provides important insight into the health of your customer base, enables you to spot trends and patterns in what’s working and what isn’t, and can help inform your strategy going forwards.
But collecting data for the sake of collecting is stupid without having a strategy to monetize that data. Good examples of strategies that can be developed are the following:
- Discover the right new customers: using behavior and customer look-alike analytics your can inform your targeting strategy.
- Nurturing of new and existing customers: insight into online or offline behavior can drive nurture campaigns to drive customers into making a first purchase
- Cross-sell, upsell and affinity models: customers build a history of interactions through service requests, product use, and other communications. You can use this insight to fuel product recommendation to customers, or products recommendations for account managers if that makes sense for your business. Lead analytics and lead scoring can prioritize incoming leads, help you acquire high quality leads and grow existing customers.
- Churn models: predict customer churn, and counter churn with churn campaigns Loyalty models: using customer data, specific strategies can be developed towards most profitable customers, or strategies to retain customers.
New segmentation criteria needed
The absolute first step in personalization is having a segmentation model . It sounds boring, and it probably is. But it is critical to have your segmentation model mapped out.
As marketers, we sit on piles of CRM data, transactional data, web-analytics and email addresses. But when we need to communicate with customers, we still take the widest possible segment because we have do not have the time, or the tools, or the insight to personalize our messages.
That’s the typical situation. Sorry to put you on the spot, but I think in the majority of marketing organizations there is little room for personalization beyond addressing someone with his/her first name. Hey, I’ve been there myself. When you go into your CRM system, it turns out your segmentation model is not entirely what you need, and you widen your segment because the list seems too small.
Do you recognize the situation? You want to personalize, but the segmentation criteria you use in your systems are not adapted. Let’s fix that by adding segmentation criteria to the model that allow us to personalize the marketing experiences of our customers.
If you would review the segmentation criteria often found in most organizations to most likely would find something like this:
- demographic segmentation: this is the most basic segmentation. This can be gender, age, income, and more.
- geographic segmentation: this is all about where the customers is located.
The segmentation that is key to making your marketing more personalized and customers centric is what I call “ customer centric segmentation criteria ”:
- psychographic criteria: this is all about who the customer really is.
- behavioral criteria: this is all about what the customer does when he is seeking the value you bring with your products or services.
Psychographic and Behavioral Segmentation Criteria
Most segmentation models contain elements on market segmentation, application and product segmentation. That’s most commonly found. Most of us also have access to CRM segmentation which gives us some contact and account segmentation, but that’s it. And transactional systems like ERP or invoicing systems give us monetary data.
The problem is that we don’t have the interests of customers in the model, nor do we have the behavior in the model… In essence, most segmentation models are built around brands , and not around customers.
That’s not really “customer centric”, is it? So let’s add a couple of customer centric segmentation criteria to make personalized marketing experiences possible…
But which segmentation criteria do we need to add? To answer that question, the easiest thing to do is to map out your current segmentation model.
- Start by making an inventory of the segmentation criteria you have today
- Cluster these segmentation criteria into product, category, marketing application, … and work your way towards more customer centric segmentation criteria you have or should have.
- Map these clusters along the customer journey.
Once you have done this exercise, it becomes clear what you are missing in your systems. You can now start implementing or updating the segmentation criteria in your different marketing systems:
- Your CRM system
- Your website content tagging
- Your marketing automation system
- Your analytics software
- Your e-commerce platform …
Linking Strategy with Data
Data is nothing without strategy to monetize the data. You might have the segmentation model ready. And you might have the data. But without a strategy to monetize this all, you won’t get zip.
Let’s take the example of a marketing organization in the retail industry.
- The business objective: the marketing managers wants to re-active lapsing customers. Lapsing customers are customers that have bought in the past, but for some reason they are buying less today.
- Micro-segmentation: to reactivate these lapsing customers, we want to address them with a contextual relevant message, because that is what is needed to win-back these lapsing customers. Using transactional data, lifestyle or interest data, and behavioral insight we build a micro-segment of these lapsing customers.
- Personalized communication: a demand generation program that runs automatically to this micro-segment will run on weekends, offering a 30% discount in the favorite category of our segment.
This is just a small example how strategy can fuel a marketing program, through data and micro-segmentation.
Usage of the segmentation model
Using the example of our marketing manager in the retail industry, we can further dive into the details of how the segmentation model can is used in the different stages of customer acquisition or retention:
- Traffic building: first drive traffic through different channels and tactics
- Engagement capturing: capture and segment the engagement behavior
- Demand generation: run personalized marketing and sales campaigns
- Experience delivery: and in the case of existing customers, run programs that bring personalized experiences
The “SUSHI” example
Each of these different stages contain different tactics. In the case of traffic building you have lot’s of possibilities, same thing goes for creating and capturing engagement. And the same goes for the other stages.
To explain what this means, let’s dive into some details by pouring the model into a real-life “sushi” example: we want to bring personalized marketing experiences to prospects that are interested in everything related to “sushi”. Our objective in this example is selling equipment like rice cookers, sushi knives, etc…
- prospects are targeted with content marketing topics about sushi, using Facebook ads, emails and pages on a website
- engagement is then captured, segmented and interpreted by ea. a marketing automation system.
- based on this engagement, personalized campaigns or “demand generation programs” are executed on one-to-one basis.
That’s it for this one. A very practical post this time, on how you can introduce more personalized marketing. Let me know what you think, and feel free to comment.
Thank you for reading. If you like this post, why not subscribe to this blog?
Tom De Baere