Tag Archives: customer

What the U.K. Can Teach on Aggregators

In the last 10 years or so, the single biggest development we have seen in U.K. personal auto insurance distribution is the phenomenal rise of aggregators – known otherwise as “price comparison websites.” Top aggregators in the U.K. marketplace such as Confused.com, Moneysupermarket.com and Comparethemarket.com have grown, leveraging the high usage of Internet among U.K. households. According to the latest industry reports, aggregators accounted for around 56% of the new motor insurance policies sales in the U.K. in 2013.

The overall potential of aggregator share in the U.K. personal auto new business is capped at around 60%, which means aggregator growth is fast approaching stagnation. Though this is evidenced by the flattening growth we are seeing in recent years when compared with earlier periods (when market share rocketed from 25% in 2007 to 45% in 2009), aggregators are here to stay – purely because U.K. customers still see cheaper cost as the major preference in choosing auto insurance.

For insurers and brokers who operate in markets with a heavy aggregator presence, the options are pretty clear and simple — either to partner with aggregators or to compete with them. There are pros and cons in both these approaches.

The advantages brought about by aggregators to customers are too obvious – exposure to a larger variety of auto insurance products, competitively priced quotes and, most importantly, an efficient purchasing process. For insurers and brokers specifically, aggregators provide medium- and small-sized players (who don’t have the scale to compete with the biggies) the opportunity to generate business by advertising their products at a low marketing cost.  Also, through their online platforms, aggregators collect large quantities of customer data around customer website visits and browsing patterns. These can be gainfully used by the insurers/brokers to build a better picture of their customers’ profile and risks as well as put in necessary checks for improving fraud control.

See Also: Driver Safety Ratings Add Sophistication

Key risks are:

  • Too much emphasis on providing the most competitively priced quote based on a minimal set of questions results in quotes incorrectly priced and a below-par underwriting performance for the insurer
  • Consumers get the ability to make purchase decisions based on what-if scenarios (like inputting lower mileage or switching then main driver to see the resultant reduction in premiums), possibly inducing them to provide incorrect information and purchasing unsuitable cover
  • Reduced due diligence at the underwriting stage associated with online policy acceptance can result in increased risk of fraudulent claims – including instances of intentional fraud such as use of stolen credit card information, dead letter box addresses and identity fraud.

Some large insurers in the U.K. have withdrawn from partnerships with aggregators to compete directly in this space. Aviva, for example, offers a quotes comparison facility on its website, while DLG encourages its customers to go online to its site to avoid paying aggregators’ commissions.

A few major factors that influence large insurers and brokers to move away from aggregators are:

  • Having a product listed consistently lower in an aggregator’s rankings is perceived by insurers as hurting their brand
  • Insurers/brokers rely on opportunities to reward customer loyalty and retention at every possible point (through cross-selling/upselling discounts, etc.) to maximize their revenues, while aggregators thrive on customer churn, leading to a possible conflict in business models and weaker customer relationships

Still, none can deny that aggregators are a fixture in the personal auto insurance business for the foreseeable future. Some larger insurers that offer auto insurance online directly to customers also agree that it’s possible to build effective partnerships with aggregators. Some ways of ensuring success through aggregator channels for insurers and brokers are:

  • Collaborate more closely with aggregators to sell on brand rather than just on price – insurers/brokers will primarily own customer relationships and have profit-sharing agreements in place that provide incentives for aggregators to cross sell more of an insurer’s products apart from auto
  • Build systems to ensure that the wealth of data from aggregators is well-utilized for smarter and more frequent pricing of auto quotes (for example, daily rather than monthly or quarterly)
  • Design and segment customized auto policies specifically for aggregators, with underwriting models reflecting the questions set
  • Ensure that the aggregator online platform is updated on a periodical basis and that all components reflect the preferences of the insurers, brokers, customers etc.

Innovation: a Need for ‘Patient Urgency’

In corporate innovation, little else matters if your timing is wrong.

Moving too fast killed Ron Johnson’s attempts to turn around J.C. Penney. Johnson plunged too quickly into a wholesale remake of the century-old chain’s stores. He didn’t take time to test alternative possibilities—even though, as the developer of the Apple stores, he experimented with every little detail for months in a mock-up before going to market. Johnson also threw out Penney’s long-standing sales strategy. He got rid of discounts—and alienated tons of existing customers—before validating that his new approach would attract enough new customers.

Moving too slowly killed Blockbuster. It ignored Netflix’s subscription-based, DVDs-by-mail model for years. Then, afraid that it was too late, it bet big on its own version even though it had dire economic and operational implications.

Precise timing, however, is a fool’s errand. Disruptive innovations, by definition, deal with future scenarios that are hard to read and where neither the right strategy nor timing is clear. How can you project customer interest for a product that customers haven’t yet seen? How can you deliver detailed timelines and budgets when new products depend on technology breakthroughs?  The strategy has to emerge over time. The timing has to be opportunistic.

To deal with the vagaries of innovation, leaders at Blockbuster, Penney and hundreds of other large-company innovation failures that I’ve studied would have benefited from a strong dose of “patient urgency.”

See Also: Does Your Culture Embrace Innovation?

Patient urgency is one of the distinguishing traits that John Sviokla and Mitch Cohen identified in their study of 120 self-made billionaires, as reported in their excellent book “The Self-Made Billionaire Effect: How Extreme Producers Create Massive Value.” Patient urgency is the combination of foresight to prepare for a big idea, willingness to wait for the right market conditions and agility to act straight away when conditions ripen.

Sviokla and Cohen found that their subjects were no better prognosticators than other people—“they cannot predict the exact right time to make an investment or to bring a product to market.” They did not, however, sit back and wait. Neither did they just jump in and hope for the best. They learned about the market, made early investments and deals, tested ideas in the market and actively made improvements and adjustments. When the market became ripe, they were ready.

The Sviokla and Cohen finding squares with my research and experience.

Reed Hastings of Netflix, for example, knew from Day One that people would eventually stream their movies over the Internet. He experimented with different versions of streaming video for more than a decade. He repeatedly killed ventures when he saw they would not quite work. When the conditions were right, he moved quickly to transform Netflix into a huge streaming business.

Google’s driverless car program is another great example of patient urgency. As I’ve discussed, driverless cars have the potential to save millions of lives and throw trillions of dollars in existing revenue up for grabs while sending a tsunami of business disruption across multiple industries. Google has methodically developed potentially differentiated technology in this fertile arena while keeping its options open on how to capture the resulting business value.

The problem for most large companies, however, is that neither “we’ll figure it as we go” nor “we’ll launch when the market is right” fit with traditional planning mindsets. Operating budgets hate uncertainty. They demand detailed, time-lined projections of human resources, costs and revenue—even when those demands just yield guesses disguised as numbers. This severely limits experimentation, adaption and risk taking.

To break the organizational tendencies that dampen corporate innovation, here are three ways to encourage patient urgency:

1. Think big. Focus on big ideas that have the potential to build massive value. Develop vivid alternative future scenarios to illuminate how existing businesses might get crushed or, in a kinder world, be transformed because of disruptive innovations. Getting everyone on the same page about the stakes involved will help the organization start earlier and bide its time longer.

2. Structure early investments like financial options rather than full-fledged go-to-market plans. Ideas that could turn into multibillion-dollar businesses do not deserve billions in investments right away. Invest millions, or even tens of thousands, to test and elaborate them. Each stage of funding should focus on clarifying key questions like whether the product can be built, whether it meets real customer needs, whether it can beat the competition and whether it makes strategic sense. The goal is to invest a little at a time to develop the idea while preserving the right but not making the commitment to launch the innovation.

3. Budget for innovation as a portfolio of options. Rather than force detailed projections for individual options, plan and budget at the portfolio level. As I’ve previously discussed, the overall allocation and prioritization of the innovation portfolio should depend on a company’s investment capabilities and competitive circumstances. This limits the overall risk while allowing flexibility to shift investments between individual initiatives based on experimental results and shifting market conditions. The portfolio approach also demands that multiple (potentially competing) options be tested—thereby short-circuiting the tendency to focus on one all-or-nothing bet.

See Also: Innovation Trends in 2016

Patient urgency avoids the large-company tendency to swing from complacency to panic. It loosens the constraints of shortsightedness and inappropriate planning models that lull large companies into thinking incrementally for too long, as Blockbuster did. It also lessens the chances of being late to the game and having to risk everything on a single desperate idea, like Penney, only to have it not pan out.

fortune telling

Fortune Telling for Insurance Industry

In the world of InsurTech, there are distribution players and there are data players. The data players are essentially doing two things:

First, they are enabling and exploiting new sources of data, such as telematics, wearables and social listening.

Second, they are processing data in completely new ways by applying data science, machine learning, artificial intelligence and high-performance computing.

The result is that, for insurers, the InsurTechs are creating opportunities for the development of new products for new customers; improved underwriting and risk management; and radically enhanced customer engagement through the claims process.

Which is why, in my humble opinion, tech-driven innovation in insurance will be data-driven.

As a result, this week I feature an Israeli start-up called Atidot, a cloud-based predictive analytics platform for actuarial and risk management…aka, the next gen of data modeling and risk assessment!

I’ve recently Skyped with CEO Dror Katzav and his co-founder Barak Bercovitz. Both have a background in the Israeli military, where they were in the technological init of the intelligence corps. Both have a background in cyber security, data science and software development.

These are two very smart cookies!

And they have applied their minds to the world of insurance and, very specifically, to data. To change the way that data is cut and diced to provide multiple insights from very different perspectives has been their purpose.

Atidot
The result is Atidot, which in Hebrew means, “fortune telling.”

What’s the problem?

Dror explained it to me:

“Insurers (or rather, actuaries) are not doing all that they could with the data they have. And there are several reasons for this.

“First, they miss the point, Insurers look at data from a statistical perspective and miss out on the insights and perspectives that can be seen from different points of view.

“Next…, the traditional modeling tools that are still being used today are cumbersome, difficult to re-model and rely heavily on manual effort. With new sources of data now available, these tools are simply inadequate to handle them.

“And third, they’re too slow. The frequency of updating the models is too long, measured in weeks and months. This is because many of the current tools are limited in scale and flexibility, unable to cater for the huge volumes of data now available to them.”

How is work done today?

Today, insurers think about key questions to ask prospective policyholders. Do you smoke? Do you drink? Do you have diabetes? What is your gender? What is your location?

Insurers map the customer’s answers onto a statistical table. This linear modeling approach provides a risk rating of a certain outcome, such as the mortality rate for a life product.

But data science does not follow a linear model. It is different and varied. Data is modeled to show different correlations of risk to key variables.

This is what Atidot does.

It applies multiple approaches simultaneously to process a much larger set of data. This will include existing data that was previously ignored, such as the day of the month the salary is paid or frequency of ATM withdrawals, through to new sources of data, such as driving behavior or activity levels.

And while it is still very new for insurers to link, for example, increased levels of activity to mortality rates, there is enough evidence to suggest that it is just a matter of time before they do. You only have to look at the number of competitions on Kaggle to see that!

This shift gets to the crux of the insurer’s problem:

Quite simply, traditional models don’t have the ability to handle the new sources of data. Nor do they have the muscle to process it.

I’ve previously covered some brilliant InsurTechs in the data space, including Quantemplate and Analyze ReFitSense is a data aggregation platform that provides insurers with a new source of data to underwrite life risk differently. The platform collects data from all major fitness and activity tracking devices. The data is then normalized (to weed out differences in the way activity is tracked) and presents the underwriter with a common score to indicate activity patterns and levels (just as Wunelli enables a driver behavior score from telematics data).

However, the challenge for insurers is knowing what to do with this data and how to handle it.

Dror put this into context for me:

“Let me give you an example from a South African life company who were building two life products – accidental disability and severe infection disease. To test our platform, we ran their traditional method alongside ours.

“We found that they had a lot of data about their customers that they were not using or taking advantage of. And even if they tried to, the actuaries did not have the means to group this data and properly assess it in their models.

“Atidot were able to group the data differently using our tech and show them how they could significantly improve the accuracy of their forecast tables.

“We showed them how they could look at data in a different way.“

This all sounded great, so I pressed Dror for examples and we started to talk about a piece of data that seemed irrelevant to a life risk assessment – the day the premium is collected.

Dror showed me a sample of data from a live pilot the company ran for a U.S. life business on a 50,000-customer sample.

It showed that customers who paid their premiums on the 14th of the month had a 20% lower lifetime value than those who paid on the 1st.

Atidot graph
By enabling multiple data models to run simultaneously and picking the best model to better understand customers, Atidot drew a relationship between data that the actuary didn’t have before. Nor would the actuary have intuitively thought of it or arrived at it through a linear modeling approach.

So, is this enough to change the way insurers rate risk? Or change the risk selection criteria for an insurer?

To answer this I turned to Alberto Chierici, co-founder of Safer and an actuarial consultant with Deloitte. He told me:

“One issue to overcome for insurers is communication to the customer and regulators. For example, in some states it is compulsory to communicate to consumers why and how rating factors (gender, age, ZIP code) are used in pricing.

“That is making many insurers reluctant to adopt machine-learning-based risk rating and pricing. Think about the example you cited about people paying the 1st of the month versus people paying the 14th – how do you explain that to customers?”

Alberto pointed me to this discussion on Kaggle to illustrate the point.

One thing is clear, the InsurTech puck is heading Atidot’s way.

 

The original version of this article appeared here.

A Practical Tool to Connect to Customers

I recently led a workshop at the BRITE Conference at Columbia University on how to connect to customers and was honored to be among speakers including Shelly Lazarus, Ogilvy’s chairman emeritus; Vikram Somaya, ESPN’s global CDO; Linda Boff, CMO of GE; and Columbia Professor and innovation thought leader Rita McGrath. Organized by faculty members David Rogers, Matt Quint and Bernd Schmitt, and now in its ninth year, BRITE promotes dialogue on top brand, innovation and technology trends across business and academia.

I’ve condensed about half the workshop into a self-directed exercise, so you can try it.

The workshop started with three premises:

  1. People-based offerings are the basis for market relevance. Product pushing cannot endure. We are doing business in an “I want” world where companies like Amazon and Apple have set an “anything is possible” standard. The standouts will be companies that know how to walk in the shoes of the people they aspire to serve. These successful brands will follow the customer’s journey through life with authenticity — not just fixated on how to push product selection and purchase.
  2. Customers wear different hats – they may be users, buyers or payers for your offering. People see different brand benefits based on their role. Building brand/customer connections requires you to parse these roles and tune into the relevant benefits. The benefits may not be the same — this matters when it comes to product, communications and experience decisions.
  3. Network thinking overrides linear thinking and action. Building a business through binary relationships with suppliers on the one hand and customers on the other hand has been supplanted by businesses driven by value networks, or “value constellations.” Once you have a clear picture of the user, buyer and payer roles, you have in hand raw material to begin to assemble the members of your constellation. More on this topic in a future post.

Growth and Transformation: The Holy Grail

There’s not a conversation I’ve had with a senior executive in the past few years – irrespective of business size or sector – that didn’t share two linked priorities: growth and transformation. Technological possibilities, customer expectations and the need for speed demand a departure from historically beneficial but now outmoded strategies.

To Solve A Big Problem, You Have to Chunk It Down

To paraphrase a favorite colleague of mine from my days at American Express, “you just have to chunk” the big, hairy problems to make progress toward solving them.

Traditional business strategy starts with questions like: “What business are we in?” and “What core competencies can we use to compete?” These are inside-out questions whose answers assume “sustainable competitive advantage” is something you can achieve and own.

Set these assumptions aside. Our economy demands you define your strategy from the “outside” — where the customer is. Twentieth-century notions of strategy revolved around your position relative to competition. Twenty-first century strategy revolves around the customer.

This means the first chunk to work at is “Who is our customer?” And next, “Can we engender a transformational relationship with our customer, starting with focusing on needs, and then align all of our activities and decisions to deliver?”

A Simple, DIY Tool to See Your Customers as People, Not Data Points

Here’s a tool you can use to deepen your brand’s connection to customer needs and begin to conceptualize new business models for enablement.

Whether you complete it in your head or around the table at a team meeting, this simple template can nudge even stubborn traditionalists to ask new questions about how customer insight translates into business results.

Milton Rokeach: The Hierarchy of Needs and the User/Buyer/Payer Model

Rokeach, a 20th-century social psychologist, conducted research resulting in an inventory of desired end states for human existence. These end states, or values, are summarized below:

POSTPeopleBased

How Does This Theory Apply to Brands and Innovation?

Brand managers tend to enumerate product features to explain value to customers. Better brand strategists get to the benefits, too. But almost always, brands stop short of the much richer territory – connecting the brand to the values people strive toward in life.

By pushing a little harder to understand which values your brand satisfies (i.e., back to Rokeach’s inventory) you can find new growth levers, and pragmatic transformation priorities can emerge.

What Does Soup Have To Do With It?

POSTsoupcan

So, in the simple example of a can of soup purchased for my family, the benefits may be a tasty, quick, low-cost meal that satisfies my daughter’s hunger and provides some nutrition. But as a mom, my values are things like fulfilling my sense of duty to family, maintaining family harmony at the dinner table, keeping my life under control and getting time back in my day. Brands that demonstrate connection to these sorts of deeper values will win my perpetual loyalty. Features and benefits are temporal. Values endure.

Next, by delineating what is sought by users vs. buyers vs. payers (and understanding what the implications are when these roles are played by different people), you will establish a new angle on segmentation and shine a light on otherwise hidden innovation opportunities.

So back to the can of soup, note the differences below between the benefits that matter to the user, the buyer and the payer. These may be one, two or more people. But even when one person plays all three roles, the benefits that one person sees through each lens are different.

Slide1

Slide1 copy

So what about features?

Features may provide reasons to believe in the brand benefits, or even ladder up to the brand values. But by themselves, they will almost never endear customers to you. And, in fact, they may burden people with detail that distracts from a quick determination of whether the brand represents a good choice. At a minimum, features must be shared for the sake of ingredient transparency – the latter representing a brand value that has gained in importance especially for millennial buyers.

Try to complete the user/buyer/template model as a team exercise or on your own. See how it can get you thinking about improving customer focus and engagement by connecting to the higher-order needs of whatever marketplace you serve.

Are Your Customers Like Berliners?

Soon after the Soviet Union erected the Berlin Wall, President Kennedy uttered the now-famous words, “Ich bin ein Berliner” (I am a Berliner). Initially, this was a statement aimed at the Russians that was intended to show Western resolve. Over the years, however, it has become adopted by Berliners as a statement of individuality and freedom of expression.

During a recent holiday in Berlin, I was reminded of this famous speech by the many historical sites I visited and the people I met. Berlin feels like a city of contradictions. Hard to categorize, it feels like an individual who refuses to be neatly pigeon-holed.

Is that true for your customers, too?

We have an armory of customer insight tools at our disposal these days (from various segmentation approaches, to predictive analytics delivering real-time personalized marketing content). It’s, perhaps, too tempting to focus on what is possible, rather than what your customers actually value. How often do you find yourself thinking about your customers in terms of stable segments or predictable behaviors your models can “understand”?

In Berlin, immersing yourself in the smorgasbord of sites, entertainment, food, drink and sheer variety of people is a great tonic for that simplification. It can also help dispel a number of misconceptions that Brits like me still have about our Anglo-Saxon cousins. Here are a few apparent contradictions that struck me:

  • You can be fined for crossing the road before the “green man” is illuminated, and most people obey this rule. That plays right into my assumption that Germans are rigid rule followers, almost control freaks. But then, as you walk around Berlin, you find a widespread acceptance of graffiti everywhere. At first, it can seem scruffy and run-down, but it seems that people value this freedom of expression, this individuality.
  • Berlin has many historical sites, beautiful museums and art galleries. Indeed, much of the information from the tourist office would lead you to expect that this classic, historical city is full of affluent middle-aged Germans and other tourists appreciating the many forms of culture the city has to offer. But, in my experience, 80% of those traveling in Berlin appear to be under 30. This is a youthful and vibrant city, with more nightlife and social venues than you could fit in your itinerary.
  • The British are famous (perhaps infamous) for believing the Germans have no sense of humor. Much of the comedy I grew up watching, including Dad’s Army, plays into such stereotypes. However, anyone attending a cabaret show called “The Wyld” will find an entertaining and hysterical cocktail of comedy, dance, circus acts and risqué performances that suits all orientations.
  • Like us Brits, the Germans are not renowned for their cuisine. People could easily assume all people in Berlin eat is currywurst (which is tastier than I expected) and beer. But this most cosmopolitan of cities has quality cuisine from all over the world. I, personally, enjoyed the food at a Jamaican-European fusion restaurant that was better than any I’ve visited in the U.K.

So, what’s my point for customer insight leaders (apart from recommending a vacation in Berlin if you haven’t been)? I want to remind you to remember that your customers are individuals whose lives will be filled with apparent contradictions. Don’t be surprised and discount research or analysis that appears to contradict what you think you already know about your customers. Rather, I’d encourage being open to insights about contradictory and changing customer wants and needs.

How do you respond to this challenge? Have you managed to stay focused on the jobs your customers want to get done—without assuming you fully understand them? Have you embedded a test-and-learn norm in your marketing that keeps your approach fresh and flexible?

Please do share your tips and tricks for avoiding stereotypes as well as any insight musings you have had from your holiday. I’d love to hear them.