The Five Problems With Personalization
Hi Al, Alex, Anne, Bob, Brad, Curt, Chris, Deborah, Doug, Emily, Jennifer, Jill, Jeff, Kim, and Frank!
(just trying to personalize this post, because I'm told that's the key to success today)
Warning: If you believe that personalization is a critical tactic impacting the future of banking, this post might not be for you (see how I'm further personalizing the post already!?). I don't buy into some of the research cited as proof of the personalization potential--but I do buy into (some of) the thoughts of one university professor on the perils of personalization.
Banks Suck at Personalization
Observers warn banking executives about a “personalization gap” in banking. According to the Digital Banking Report:
“Consumers expect their financial institution to understand their needs and deliver personalized solutions similar to what they receive from new financial providers (Fintechs) and the Big Tech firms. Unfortunately, even with enviable stores of data and advanced analytic capability, most personalization expectations remain unfulfilled. As consumers become increasingly demanding around their expectations for an intelligent personalized experience, significant ‘personalization gaps’ are appearing between what consumers want and what financial firms are delivering.”
There's no way to soften the blow on this one. Banks are lousy at personalization--and they know it. Just a quarter think they have advanced personalization capabilities for alerting customers in real-time about unusual account activity--and the percentage that think they have advanced capabilities for other personalization activities goes down from there.
What Do Consumers Want?
A study from InMoment asked consumers what their preferred form of personalization is, giving them the option to select one of three different types of personalization: support, purchase journey, or advertising.
The InMoment study defined support as:
"Staff who are knowledgeable of products and services, recognizing past purchasing patterns and needs and aware of loyalty membership."
It's interesting to note that consumers'--even (and especially) 18 to 34 year olds'--preferred method of retail personalization was human-based.
Barriers to Personalization
Financial services executives see some barriers to personalization, with too few personnel dedicated to personalization at the top of the list.
This is nonsense. How is throwing more bodies at personalization going to solve anything? And why aren’t the following elements on the list:
- “Having the right data to drive personalization efforts” and
- “Understanding what the customer wants personalized”
You won’t convince me they’re not on the list because banks have them all figured out already.
What Should Banks Do to Personalize (According to the Consultants)?
McKinsey's prescription for personalization is quite simple (conceptually, at least).
It's oh-so-simple, isn't it? You just need to :
- Assemble rich data. Don't even think about using the "poor" data you have. It won't help you personalize.
- Mine data to identify consumer signals along the journey. Never mind the fact that you don't have much of the data that consumers generate along their "journey."
- Test and learn in an agile way. The lethargic way in which you've been testing and learning won't cut it anymore!
- Measure and embed learnings in existing systems. What does this even mean?
Five Problems With Personalization
So far we've determined that the perceived barriers to personalization are nonsense and that the prescription for personalization is incomprehensible and undoable. Wait--it gets worse.
In a report titled Five Fears About Mass Predictive Personalisation in an Age of Surveillance Capitalism, Karen Yeung, an Interdisciplinary Professorial Fellow in Law, Ethics and Informatics at the University of Birmingham identifies a number of problems with the whole concept of personalization:
1) Exploitation. As Yeung writes:
"Personalization practices foster and exacerbate the asymmetry of power between profilers and those to whom personalized services are provided, thereby increasing the opportunities for the former to exploit the latter. Tech firms are already developing billboards that can recognize and categorize individuals, then demographically direct personalized messages. Analysis of the click-through behavior of individuals can readily identify when individuals are feeling low, more likely to make impulse purchases, or more susceptible to particular kinds of offers, enabling retailers to exploit detailed knowledge inferred from user profiles to micro-target personalized offers in ways that will maximize the opportunities to make a sale."
2) Manipulation. With traditional service personalization (e.g., having a suit custom-made), consumers explicitly state their desires and preferences for a personalized product or service. In contrast, the new digital approach to personalization is to infer desires and preferences, "not only before the individual has requested the service, but often without the relevant individual requesting such a service at all." According to Yeung:
"Because the individual has not explicitly stated her preferences and interests about the service in question (indeed, she may not want the service at all), predictive personalization techniques may not be in the interests of the customer. Predictive profiling systems employ ‘nudging’ techniques which intentionally seek to exploit the systematic tendency of individuals to rely on cognitive heuristics or mental short-cuts in making decisions, rather than arriving at them through conscious, reflective deliberation. Nudging techniques are problematic because when used for the purposes of mass predictive personalization, their manipulative power is enhanced."
3) Marginalization. Yeung claims that "individuals who score highly in algorithmic rankings are likely to benefit in the form of generous and attractive offers and opportunities, those who score poorly, and are thus deemed poor prospects for marketers and retailers alike, are likely to be disadvantaged and disempowered by the turn to mass personalization."
The complexity with which data is used and analyzed for personalization purposes makes it nearly impossible for people to understand why particular services are offered to them. Yeung cites a Carnegie Mellon study which found that men were shown high-paying job ads six times more often than women based on an algorithmic assessment that concluded that women weren't interested in high-paying jobs because they had historically not been employed in them.
4) Injustice. Yeung argues that:
"The aggregate and cumulative effect of mass personalization over time is likely to contribute to and exacerbate social inequality and distributive injustice. By providing marketers with the technological capacity to segment consumers into distinct groups based on their relative value and profitability to the retailer, these technologies enable sellers to engage in a commercially rational form of social sorting, seeking to cultivate and attract the choicest customers and exclude low-value customers."
5) Narcissism. Yeung believes that personalization will "fuel a culture of narcissism, prioritizing economic morality over social equality thus eroding solidarity and community." She argues that:
"Deployed at scale, the way in which data-driven personalization techniques are being applied to maximize the economic ‘value proposition’ for organizations that utilize them is likely to: 1) Foster a cult of the individual that signifies a shift from a culture of capitalism that can be understood as moving beyond a cultural of material consumerism to one of narcissism, and 2) Corrode social solidarity and so loosen our social bonds that it could threaten the very nature of our collective character as a moral and political community."
It's time to rethink and be honest about the promise of personalization. Do the promised benefits--to both marketers and consumers--really live up to the hype? Are they even achievable in the short term? And are they worth the costs--both in terms of the technology investments required and the potential negative societal impacts?
Let's recap what we've learned here:
- Banks suck at personalization.
- They think they suck because they don't have enough people dedicated to the effort.
- The prescription to personalizing (at scales) involves a bunch of consultant-gibberish.
- Personalization may lead to exploitation, manipulation, marginalization, injustice, and narcissism.
This is a mess. And I think it's avoidable if banks focus on:
- Segmentalization. The stated objective of personalization (in some camps) is to achieve a "segment of one." For a bank, is that a realistic objective? At what cost could it be achieved? Answers: It's not, and at an exorbitantly high cost. Instead, banks should focus on defining meaningful (i.e., sufficiently large enough and different enough) segments of consumers to serve. By defining the unique product and service needs of a particular segment, consumers that fall into that segment will believe the bank is "personalizing" their offering to them. And isn't that what banks are trying to achieve by personalization, anyway?
- Product design. Personalization via alerts, offers, and advice are problematic. Consumers get a gazillion offers a day. They're hard pressed to know which are driven by personalization and which aren't. And for better or worse, consumers have shown little interest in getting advice from their banks, and the banks (generally speaking) lack the data to do it. What banks can do is focus on product design, and design deposit and lending products for specific segments.
Director of Research