Let’s call it the new form of mass marketing. What we do today is reach individuals at scale. People expect to be treated like people, not anonymous buyers. This shift in consumer expectations requires an overhaul of customer messaging. It’s not just a content challenge – although there is a lot of good old-fashioned brand strategy involved here, it starts with a segmentation challenge. Our segmentation strategies create the language for interpreting and addressing customers’ needs.
Back in the day, a segmentation strategy could work using standard attributes: demographic, geographic, and purchase behavior. The limitations forced marketers to think in terms of brand value, not personal value. We created personas to guide our thinking, but we grouped together people by their relationship to our brand, not by their individual characteristics. Today, advanced data matching and automation technology let us shift to a more individual approach.
As any casual observer of human behavior will tell you, people do not always behave logically – the way their static demographic of past buying data suggests. Emotion plays a pretty big role in purchase – and many customers are craving emotional connections through rich and authentic brand experiences. A good example is the small craft brands in beauty and cleaning products making headway against Procter & Gamble specifically because customers want to interact with real people.
Research from the Corporate Executive Board (CEB) and Google found that customers with strong connections to B2B brands have higher rates of consideration, purchase, and willingness to pay a premium. After surveying 3,000 B2B buyers from 36 distinct brands, the CEB found that emotions trump rational motivators by a two-to-one ratio. The report found that “Today’s customer-centric branding appears to be working: most B2B buyers (74 percent) now believe that brands will provide business value.”
This trend seems to be resonating with marketers. About 80 percent of B2B marketers say they can gauge which customers are their most valuable, according to a recent report from Regalix. Some 64 percent say they understand customers’ past purchase behaviors, but only 48 percent say they have an “excellent understanding” of the customer demographics.
If marketers start using more emotion in their messaging, the importance of exact imagery and language grows. That means content has to be aligned to individual preferences, not groupthink. The automation technology can work really hard for us – executing complex segmentations, aligning campaigns to each segment across a dialog or drip marketing approach, scoring leads based on real attributes, and tracking success in to allow rapid course correction.
But technology is nothing without great strategy. There are two key foundations to ensuring your segmentation, campaign management, and automation technology is working hardest for you:
- Segment at the individual level based on highest-value customers, and reach them across the channels they are most interested in. Here’s a simple way to calculate lifetime value (LTV):
(Average Value of a Sale) X (Number of Repeat Transactions) X (Average Retention Time in Months, or Years, for a Typical Customer) = LTV Score
Let’s say BMW runs an online ad campaign and knows a qualified visitor has arrived on the website – in this case, a business executive with a six-figure salary who is located within 10 miles of a dealer. BMW can serve an ad with a high-value leasing offer. Using CRM retargeting, BMW can both reconnect with this individual, and use the behavior to identify other known high-value people.
Post purchase, BMW could identify this person doing another high-value activity – say shopping for hotels in a nearby destination – and serve a display ad with an exclusive offer for a month of free Sirius Radio (compliments of BMW) for the upcoming road trip.
That level of customization requires being able to recognize a high-value customer (scoring), segmenting the messaging to ensure the right offer is delivered (campaign management) and integrating the data across channels to allow for programmatic display advertising (CRM retargeting).
- Think about customers first. Be smart about the questions you ask of your database, in order to improve the segmentation and scoring models:
- What data sets can be attributed to each customer? How can these distinctions be used to create customized messaging across various touch points?
- What products are most preferred by individuals of a certain score and attribute set, in a particular life stage?
- Which opportunities convert best and under what conditions? And which opportunities remain “stuck”?
- What is unique about the product segments that have the fastest traction and adoption?
- What are the usage patterns of high-value people? What other channels do they access? Are there upsell opportunities that can be optimized?
- Which messaging and content is most accessed? Shared? When?
How is emotion affecting your segmentation and marketing automation? Are you adapting your models to connect with high-value individuals, treating them like people first, and buyers second? What is holding you back? Please comment below to share your ideas.
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