Emerging technologies make it possible to move segmentation and personalization models beyond marketing personas to distinct, individual customer profiles.
The ability to collect customer information, organize it (i.e., big data), and draw insights from it (i.e., machine learning) makes it possible for marketers to evolve.
This evolution from buyer personas to individual profiles can provide superior personalization and an enhanced experience for shoppers. In turn, if retailers offer a more personalized shopping experience, they may sell more products.
Marketing Personas
Marketing personas are composite sketches or representations of your business’s most important customer segments. These sketches stem from information about your customers’ demographics, behavior, and motivation. This customer data is collected, analyzed, aggregated, and organized into groups or cohorts. These cohorts become the building blocks for a buyer persona.
Personas organize shoppers into groups. Although marketers will speak about personas by individual names, such as “Tom,” the data is a composite of that group.
For example, a retailer that sells workwear from brands such as Carhartt, Walls, Dickies, or Berne might have a marketing persona like this.
| NAME: | Tom |
| OCCUPATION: | Construction foreman |
| INCOME: | $52,000 per year |
| AGE: | 42 |
| GENDER: | Male |
| RELATIONSHIP: | Married with children |
| HABITATION: | Suburban home owner |
| REGION: | Pacific Northwest |
| EDUCATION: | High school, some college |
| GOALS: | Comfort on the job, durability, acceptance within peer group |
The “Tom” persona could guide some marketing decisions.
Personas help us understand groups of customers and prospects, which enables us to (a) deliver relevant marketing messages, (b) segment email lists, and (c) decide what to write about in a blog post.
In fact, personas are now and will likely remain an important marketing tool, but they are not the end of customer understanding.
Personalization
Personas help marketers understand or think about groups of shoppers. This approach is a lot better than just making guesses about what shoppers want.
Guessing, unfortunately, is what a lot of retailers do.
With personas, marketers don’t have to rely on anecdotes or someone’s opinion. Rather, personas use real data to draw insights about groups of people, which are helpful for marketing and customer experience. But it doesn’t always go far enough.
While the persona for “Tom” may describe what individuals in this group generally have in common — such as occupation or location — it still ignores distinctions within the cohort. Personas almost make stereotypes of customer groups.
Marketers may think that just because folks in the “Tom” persona have some things in common, they will have everything in common. But that is not necessarily true.
Thus, there is the need to move beyond organizing shoppers into groups and market to individuals in unique ways. This is a trend that has a few names and several distinctions. Some refer to it as me-commerce, personalization, extreme personalization, or individualization. But the goal is the same: Treat shoppers like individuals.
Individual Profiles
The movement from personas to profiles begins with collecting much more comprehensive, even real-time, customer information across all sales channels and interactions and placing all of it in a single database, where it can be analyzed and used to draw conclusions not about a group of people, but rather about individual people.
This will require significantly more engagement with customers, as marketers will need to ask for personal information in exchange for the promise of improved customer experience.
The information collected will be similar to the items used to describe a persona. But rather than generalizing this information to describe a group, the marketer will store it for a single customer.
This profile could include:
- The customer’s name, email address, and physical address.
- Demographic information, such as gender, age, relationship.
- Social media identity, including a Facebook profile and similar.
- Behavioral data — interactions and transactions.
- Sentiment inferences from reviews and social posts.
- Membership in groups or organizations.
- Public record data.
Data Collection
The technology exists to collect and understand customer information, but it may require integration and development.
For example, cloud services such as Amazon Web Services and the Google Cloud Platform have the tools to develop comprehensive, individualized customer profiles, to market directly to specific shoppers across retail channels.
There are also comprehensive software solutions that enable customer individualization, opening up profiles and one-to-one marketing. But these solutions are still emerging and may be aimed — for the time being — at large companies.
Using Profiles
Customer profiles can enable comprehensive, individualized marketing.
For example, imagine an omnichannel retailer with physical stores and an ecommerce site. Two shoppers go online and look at a Carhartt brown duck work jacket. One shopper then goes to a physical store and buys the jacket. The other does not.
This retailer may want to remarket the Carhartt jacket to the non-buying shopper with on-site merchandising and email. For the shopper who completed the purchase, the retailer could remarket with complementary products, such as pants, shirts, or hats. The retailer would not be marketing to a “Tom” persona, but to actual individuals.
Similarly, if the shopper who had not yet purchased posted on Facebook about running in, say, a Susan G. Komen “Race for the Cure” event, the retailer might send an email message offering to donate to that organization.