A digital persona uses data, machine learning and networked devices to tailor messages and experiences to specific kinds of buyers and users. At DMI, we’re big believers in digital personas because they help us zero in on the people who actually use the mobile systems we design and implement.
The ultimate goal of a digital persona is to achieve the marketer’s dream: a segment of one. Conventional marketing uses buyer personas to tailor messaging to segments numbering in the thousands or millions. But a lot of that messaging is wasted on non-buyers.
With a segment of one, you know exactly what the consumer wants because you understand their motivations and interests and you can send relevant messages that match the context of their lived experience. You can sell at the precise moment when they’re ready to buy and avoid wasting time and money on the uninterested.
It sounds like a marketing unicorn, but it’s closer than you might suspect, thanks to the potential of digital personas.
How a digital persona works
An analog persona captures core demographic data like age, gender, location and career. It also identifies interests, motivations, objections and factors that encourage a purchase. It’s essential to message targeting, but a substantial volume of the messaging misses the bullseye because it can’t account for the buyer’s real-time circumstances.
Digital personas overcome this shortcoming because they pull from data mobile devices that always relay data on time and location. Moreover, people’s purchases and travels provide key insights on their behavior patterns. All their device apps generate even more data revealing their intent in more granular detail.
At DMI, we use digital personas to serve up mobile services that match the context of people’s activities. It’s a perfect fit for retailing because people’s past purchases tend to predict what they’ll buy in the future. But personas also can customize workplace experiences so that different employees get different user interfaces, each one capable of updating in real time to match the kind of work they’re doing.
In the store, you get more sales and more satisfied customers. In the workplace, you get more efficiency and less frustration, which boosts profitability and reduces turnover.
Machine learning, business logic and data science are crucial
Mobile device users generate mountains of data that must be sifted for relevant insights and applied in real time. That simply cannot be done without advanced machine-learning algorithms and data-science modeling.
Imagine this scenario: Somebody buys your smartphone and calls your technical support line to answer a setup question. A digital persona can see this buyer’s previous purchases and online travels, and predict with a fair degree of accuracy why they’re calling. Your tech-support rep can have real-time access to a summary of this data, resolving the problem faster and making your contact center more efficient. Multiply this scenario by millions of interactions and it all adds up.
To make digital personas work, you need to strategically apply machine learning algorithms that use microservices and APIs to anticipate users’ needs and satisfy them in the context of their current time, place and behaviors. That’s an immense technical challenge that should not be underestimated.
Privacy and governance
As the furor over Facebook’s use of private data revealed, consumers are uneasy about many facets of personalization. The start of GDPR in Europe underscored the lengths to which regulators will go to protect people’s personal data.
Because gathering and exploiting people’s data without their permission generates ill will and regulatory pushback, it’s a good idea to develop opt-in programs that deliver customized experiences only to those who ask for them. Moreover, strong cyber defense and comprehensive data governance are fundamental to making personalization effective.
On the way to a segment-of-one future
When you see online ads this week encouraging you to purchase products you bought last week, it’s easy to dismiss the potential of personalization. But we’re only in the opening paragraphs of this story.
As machine learning algorithms get better at parsing user interactions and predicting future behaviors, we’ll get much closer to segment-of-one functionality. Digital personas will be a catalyst in that evolution.
Michael Diettrick, SVP of Digital Stratey, Chief Digital Officer