| Type | Definition | Identify online by | Recommended real-time experience personalization |
|---|---|---|---|
| The Explorers | Are open to new ideas and concepts currently unaware of; often passively consume content. |
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| Satisficers | Are not a hard sell once they encounter a good enough product that meets their criteria. |
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| Type | Definition | Identify online by | Recommended real-time experience personalization |
|---|---|---|---|
| Goal Oriented Visitors | Have a good idea of what they want, but may need assistance finding it |
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| Maximizers | Need to feel in control and aren’t confident until they’ve explored every possible option, often paralyzing them and inhibiting their decision making capabilities |
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Web personalization is based on a set of rules and algorithmic laws that drive each visitor’s experience. To deliver engaging online experiences, it must be effective enough to recreate the one-on-one interaction available in a brick and mortar store.
So, we create thousands of variations to tailor recommendations out of vast product catalogs, relying on sophisticated algorithms and machine learning to take into account a visitor’s product affinities, behavior, and numerous other data-points.
However, when we need to program a personalized experience among a few authored variations, such as determining the number of products to display on category pages, we tend to conjure up and fall back on “personas.”
These various fictional and over-generalized human prototypes represent types of shoppers. For example:
But, while a website or an app might be able to automate environments managed by machines, the shopper sitting on the other end is fully human. Thus, we have to work harder to address the changing needs and swinging moods that fall outside of these flat personas which can make or break an online purchase.
As we see them today, personas succeed at a few jobs:
Other than that, the static and constant nature of these personas quickly becomes limited when seeking to tap into and impact the buyers’ decision-making process. The buyer persona is dynamic and dependent on several real-time factors:
The persona must be adapted to include these in-the-moment data points. Additionally, it should fluctuate based on changes in attitude and intent, allowing it to encapsulate a more comprehensive picture of the person(a) who actually makes the purchase.
That being, the decision-making persona.
Following best practices, brick and mortar sales assistants are ordinarily trained to adapt their approach and level of service to the shopper’s needs, preferences, and decision-making process.
In situations where they do not have prior familiarity with a shopper’s background and preferences, these “personalization” skills become critical and must be honed around their ad-hoc needs, mood, and time considerations at that moment.
Considering a few separate scenarios, let’s identify and define a few of these ad-hoc personas, extracting key differentiators, and providing a few examples of how you can target them with an appropriate experience in real-time.
On Sunday morning, a shopper sets out to the streets of Manhattan to buy a pair of running shoes. Not a big shopper, she finds the task of identifying the right product and making the purchasing decision quite daunting. As such, she wants to be left alone to examine the goods until she finds a suitable pair, not wanting to be pressured by salespeople.
Unfortunately, within the first five minutes in the shoe store, three different sales assistants approach to offer their expertise; volunteering information about new footwear collections, hovering around as the shopper sifts through price tags. Becoming irritated, she decides to leave and go online to browse quietly without interruptions.
A persona who is open to new ideas and concepts currently unaware of.
A wife sends her husband out to buy a printer with a budget of $100, a preference for the HP brand name, and one requirement being that of photocopying capabilities. This shopper wanted to be efficient and waste as little time as possible exploring all of the available options and was, therefore, eager to receive assistance the moment he walked into the store.
In need of a sales rep who could show him the relevant models matching his criteria as well as explain the pros and cons of each to help facilitate his decision amongst a variety of options, the first two reps knew very little about this type of product and seemed to ignore the shopper’s questions. By the time the third rep arrived, he was so disappointed with the in-store experience, he decided to visit HP’s website and buy the printer online.
A persona who has a good idea of what they want yet needs assistance finding it.
Whatever the scenario, personas must evolve to match the ever-demanding needs of consumers, be it in-store or on the web. This level of omnichannel retailing will only happen when marketers adapt their strategies and tune into real-time signals, mapping experiences beyond basic demographics and pre-defined sets of rules to what really gives shoppers substance — their preferences, behaviors, and habits in the moment. That’s where the decision making happens.
