Does this sound familiar?
You and your significant other have plans to go out on a Friday night. One of you has a very specific expectation for the date night but wants the other to make the plans on their own, while still meeting some unarticulated expectation. It’s not mind reading but may as well be—the planning partner is playing a guessing game, working off assumptions, which inevitably leads to the anticipating partner’s disappointment.
As marketers, we are participating in a similar cycle. The big buzzwords in the modern marketer’s toolkit are “persona-based segments” and “journey maps,” which put customers into boxes based on assumptions.
But what if we could remove the guessing game?
Don't Waste Resources on a Maybe
How do you really understand what your customer wants? Just like in our date night example, marketers typically only see how the customer interacts with us—not what he or she is thinking or feeling.
Take Jane. She's 28-years-old with an annual income of $55,000, and she has her bachelor’s degree from a four-year college. Jane visits your store and sees racks and shelves overloaded with articles of clothing. She looks to her right and left trying to figure out where to begin. She seeks the advice of a sales associate, but it’s not clear who she should talk to. Eventually, she is pointed towards the “on sale” section. She spots one blouse; however, after struggling to move the disorganized hangers in the third rack, she gives up and decides, “One blouse is a success,” and heads to the checkout line. The sales associate at the register asks Jane, “Did you find everything okay?” Because Jane is a little shy and would rather be polite, she responds, “Yes, thank you.”
Because of this interaction, the sales associate assumes that Jane had a successful shopping experience at her store.
Based on how this store traditionally categorizes customers, they place Jane into a segment. Let’s call it Segment W. Segment W makes the broad assumptions that all women between the age of 18 and 35, who have a median income of $55,000 and have achieved a higher education have the same needs and will respond the same way to one target message. This strategy may result in a few wins, but more often than not will ultimately miss the mark.
Consider an alternative scenario where we make a different set of assumptions for Jane. Through a conversation with the sales associate, you find out that she came into your store to look for an outfit for a date night out with her significant other. Just by having a few more personalized details about Jane, your sales associate was able to sell an entire outfit, rather than just a single blouse, and provide a more directed and personalized shopping experience for Jane.
Rethink Customer Segments with Outcome Driven Insights
With the Outcome Driven Insights® (ODI) approach, businesses are rethinking customer segments, removing the guessing game, and targeting customer journey improvements with scientific precision, resulting in an 86% win rate. With over two decades of development, the ODI approach leaves behind the current segmentation methods—stereotyping users based on age, gender, income, and education to create personas—instead, focusing on the customer’s job-to-be-done.
Using the ODI approach allows you to ask your customer:
- What is the customer trying to accomplish in the store?
- Where are their needs not being met across their journey, and which of these needs are the most important?
- Where are they getting too much help across the journey?
- Are they making this purchase for themselves or for someone else?
- How important is the customer’s budget?
- How much time are they willing to spend to make the right purchasing decision for their needs?
By investigating these aspects of a customer’s buying experience through robust research methods, the ODI approach can quantitatively map out where your customers are being overserved and underserved and segment them based on this scale into needs-based segments.
Let’s revisit Jane. Through our ODI research methods, we find that Jane's key constraints are time and budget. For Jane, it’s very difficult to get the key information she needs to make a purchasing decision. This information allows us to place her in Segment C which includes men and women of all ages, income levels, and educational backgrounds.
Segment C is the most underserved Segment. It is comprised of fashion-forward individuals who keep up with the trends but are very busy and rely more on their friends and co-workers than other retail customers to make their purchasing decisions. These customers are also stronger repeat buyers, who are price conscious, yet willing to pay 20% more, respectively, if their needs are fully met.
With all of this information in hand, we now know that overcrowded racks and lack of helpful sales associates would equate to a negative shopping experience for Jane and others in Segment C.
Use Needs-Based Segmentation to Improve the Experience
The good news for your brand: there is an incredible opportunity to focus on this segment and stand out from the rest. Leveraging the insights from the ODI approach, let’s reorganize the store experience from above to meet Segment C and Jane’s needs.
No longer do we need to guess at Jane's satisfaction with her shopping experience—we know she is underserved at certain points in the buyer's journey and can work to fix it. This time, when Jane walks into the store, she is greeted right away by a sales associate who asks, “How may I help you today?” The store has been designed to feel spacious and organized, there are no overflowing shelves and disorganized racks to overwhelm her. With the information provided by Jane, the sales associate is able to take her to a small section where, she can quickly find blouses, pants, and even some dresses that she would like to try on. This section is ideal for customers like Jane—the articles of clothing are in a medium-to-low price range but are still good quality items that will not need to be replaced in the next few months. And because there is not an overwhelming amount of options, Jane saves time as well as money, which makes for a very happy customer.
To read more about our ODI-based research into underserved retail segments, check out: Can Bricks and Mortar Compete with Online Retailing?