OBSERVATIONS FROM THE FINTECH SNARK TANK
In an article titled Do Neobanks Spark Joy in their Users? AI Gives Us the Answer, Richard Turrin, author of Innovation Lab Excellence, makes the case that in the UK banking industry:
Neobanks are giving the incumbents a good beating when it comes to designing software that people want to use, and net significantly higher average ratings.”
Turrin based his case, in large part, on user reviews in the Apple and Google apps stores.
One reader of the article encouraged Turrin to repeat the analysis for US-based neobanks and financial institutions–a suggestion I seconded. But I did encourage him to find a different source of satisfaction data than the App Store ratings, which I accused of not being a representative sample of apps users.
[The app store is] probably one of the best sources of unbiased data. Ratings better represent the tails of the distribution and in doing so give us a good indication of the distributions shape and size. Not perfect, but they work. Users have to be motivated to put a recommendation up.”
Three reactions to that response:
- The claim that app stores reviews are “one of the best sources of unbiased data” has no statistical evidence to back it up. No one can prove the data is unbiased. It may be the best source of data, but that doesn’t make the data statistically reliable.
- App store ratings may “better represent the tails of the distribution” but they don’t help determine the shape and size of the tails.
- The statement that “users have to be motivated to recommend” is spot on. But there’s more to that statement than meets the eye.
The Review/Referral Threshold
The simple reason why people refer or review is that they’re motivated to. What’s more complex is understanding why, and what motivates them to do so.
Water boils at 212 degrees Farenheit. Think of that as the boiling threshold. People have a referral or review threshold. It’s the point at which they’re motivated to make a referral or post a review.
We all have different thresholds for providing reviews and referrals.
Demographics Drive Behavior
Consumer studies have found that younger consumers are more likely to refer products than older consumers are. For example, Annex Cloud discovered:
Millennials are around 2.5 times more likely than boomers to share a social media link that references a brand or product and to follow brands on Twitter.”
Product review behavior varies by generation, as well. A study from Bazaarvoice found:
When it comes to contributing negative reviews, one age group stands out as being more negative than most–Millennials.”
Intrinsic Motivations Drive Behavior
There are various reasons why people leave a review or provide a referral. It’s not as simple as they “liked or disliked the product or experience.”
There are intrinsic motivations that drive the behavior. For example, someone might wish to be seen as an expert in a given area (food, technology, etc.) and provide referrals or reviews in order to satisfy that motivation.
People with a high need to seen as an expert have a lower review/referral threshold, which skews the sample of reviewers and referrers.
Experiential Motivations Drive Review and Referral Behavior
Experience is another trigger that can bring someone to the referral/review threshold. Experiential motivation comes in different forms:
- Economic. If a company offers to pay people to provide reviews and referrals, consumers might do so depending on how much the firm is willing to pay, regarding of what consumers think about the company or their experience with the firm.
- Single experience. When the quality of a single experience exceeds expectations by some amount (which differs by person, of course), people are often motivated to provide a referral.
- Cumulative experience. Often, a single experience isn’t special enough to warrant a referral or review. But consistent, repeated superior interactions might be differentiating enough to motivate someone to refer a brand. For example, a restaurant that consistently offers good food with good service at reasonable prices is a rarity where I live. No one meal might trigger a referral, but consistency over time might do so.
People may refer and review because they see it as a way of saying thank you to the brand for exceeding their expectations, because they have a need to express themselves, and/or because they have a desire to be perceived in a certain way.
The Hidden Agendas
Referrals and reviews are clues to–and part of–the stories that customers tell. The comment itself—positive or negative—is important, of course, but is just one piece of the puzzle of understanding why someone left a review or made a referral .
Evaluating product review or referral behavior without considering the hidden agendas–the demographics, intrinsic, and experiential motivations–of reviewers and referrers leads to skewed conclusions.
So What Does This Have to Do With Neobanks’ Apps Ratings?
By just looking at App Store ratings, there’s simply no way to know if the reviews come from representative samples of neobanks and incumbent banks’ customers. The realization that consumers have different motivations for leaving a review or providing a referral adds to the difficulty in using App Store ratings to compare the two groups.
Is there a better approach for comparing the neobanks’ apps to the incumbents’? It wouldn’t be perfect, but an objective methodology that compares features, functions, and usability would be a preferable approach to relying on Apps Store reviews.