Tag Archives: Analytics

Is your competition eating your lunch in social media?

A leading bank discovered it was losing customers to an aggressive competitor. The method was simple: whenever the competitor saw a customer complaining about the leading bank on Twitter, they invited him or her to change banks.

The tactic worked only too well to be ignored.

Higland straight kitten and Dalmatian puppy eating from a bowl

Image: istockphoto.com

The morale of the story: if you want to make the most of the web, you don’t just monitor what people say about you online. You need to take action based on what you learn from those discussions.

Furthermore, you are not limited to monitoring what people say about your company. Everything that you can monitor about your own company, you can also monitor about your competitors.

Therefore, it’s no wonder that most organizations, large and small, are now monitoring social media, and in fact not just social media but the web as a whole. There are literally hundreds of tools and services out there to offer you social media monitoring and analysis.

Accuracy of social media monitoring determines your success

In order for monitoring to be useful, though, the tools that we use must come with advanced analytics.

Imagine the following scenario. You want to measure brand sentiment on the web and categorize brand mentions into positive, negative or neutral. Easy, right?

You go ahead and try one of the free social media monitoring tools, for example  socialmention.com, and stumble upon the first problem – noise. Noise is for example if you’re measuring online mentions for Santander (a bank), but your monitoring tool includes mentions of the Spanish city of Santander in your results.

If your monitoring tool is not able to filter out the irrelevant content, imagine what happens to the reliability of your sentiment analysis. Garbage in, garbage out, as the old saying goes. So you’ll need a good filter that is able to stop the irrelevant stuff from contaminating your sentiment analysis – and your own professional reputation.

Check out the amount of noise that your monitoring tool will capture if you work for – or compete with – for example If (insurance), SAS (airline, software, military), or 3 (telco operator).

Enter text analytics and natural language processing

Having filtered out the noise, your tool needs to figure out which statements are positive, negative or neutral about your organization.

Are the words “high” or “low” positive or negative? There’s no way to know if you don’t know the context of the word. This is why your analytics tool needs some heavy duty text analytics as well as what they call natural language processing. You will want your analytics tool to be able to capture and understand not only individual words, but terms and phrases consisting of several words.

Your tool also needs to understand the structure of your language, or many languages, if you are an international company.

For example, if our bank’s customer writes about “a high interest rate”, we don’t know if he or she is happy or unhappy. Your analytics tool needs to figure out if the person is talking about his home loan or his bank account.

These are just some of the reasons why you’ll want your (social) media monitoring and analytics tool to come from someone who is strong in advanced analytics.

Accuracy of measurement is key, whether it’s about brand sentiment or other social media metrics. Without good accuracy, you can’t take any meaningful business action based on your monitoring.

Our bank under attack revisited

So what happened to our friends in the bank that was losing its customers to an aggressive competitor?

They started using a social media analytics tool that captured and analyzed customer complaints in real time. As a result, they are now able to contact dissatisfied customers immediately and prevent the competitor from stealing their customers.

Posted previously in BI Blogg, Norway’s leading business intelligence website http://biblogg.no/2012/06/15/is-your-competition-eating-your-lunch-in-social-media/   

The coming merger of database marketing and digital marketing

If you ask me, the ”mobile supercookie” deserves the prize for this week’s most innovative new marketing tech term.

That being said, I was more excited to read what the Verizon-AOL merger means in terms of ad targeting, according to the same article.

It seems like yet another example of a rising trend, namely traditional database marketing and digital marketing coming together. That’s a biggie.

So firstly, in the Verizon-AOL merger you have an ad network (AOL Advertising Network), tracking your browsing behavior with something called a third-party cookie. These cookies are handy as they allow good targeting of ads. When executed well, this is good for both the advertiser and the consumer as ads become more relevant.

However, third-party cookies are also relatively easy for the consumer to block. You just adjust your browser settings. Then you’ll get only those cookies that allow you to use internet banking, ecommerce sites etc.

The bigger weakness with third-party cookies is that they track an anonymous consumer. They know what you do on the web but they don’t know who you are. This has been pretty much the norm in web analytics and marketing.

Enter the Verizon ”mobile supercookie”.

Beginning next month, instead of just the ad network, there’s also your mobile carrier tracking your web browsing. This is powerful because now it’s about an identified customer.

In addition, the browsing data will be combined with data from Verizon’s customer database, for example address, age, gender, interests, location and app usage. This opens a whole new world of opportunities for targeted marketing messages.

But, Verizon-AOL is just one example of a trend.

The world of digital marketing and that of database marketing have traditionally lived pretty much apart from each other. They have mostly been practiced by different people with different mindsets.

Now we’re increasingly seeing customer data in a company’s customer database being merged with digital marketing data which so far has been mostly non-customer-specific.

This will be the norm rather than the exception in a not-so-distant future.

”I like your HIV status”

Today’s news in the health data business is that Facebook is planning to enter the game.

While monetizing health data by creating health apps and communities has proven difficult for insurance companies, it won’t be a walk in the park for the other players, either.

The insurance company needs a less intimidating intermediary to inspire consumers to share their health data. Candidates for such an intermediary include Apple, Google and Facebook.

Even these companies will need to work hard to dilute consumers’ fears of their data ending up in unwanted places, whether it’s through hackers, criminals, nation-state actors – or by new business models that Apple & co will come up with in order to monetize their customers’ health data.

We can already see these new business models emerging, for example through Mayo Clinic’s announcement of their app and Apple HealthKit sharing data between them.

One of the comments to the article about Facebook summarizes the privacy challenge brilliantly: ”I like your HIV status”.

Does the failure of Aetna’s CarePass platform mean Apple’s platform won’t succeed?

Aetna, the American insurance giant, recently announced the ramping down of CarePass, their digital health data platform. Some commentators speculate this could mean that Apple’s and others’ similar platforms are not viable.

I beg to disagree.

For those not familiar with Aetna’s initiative, CarePass is an app that integrates with a host of services collecting consumers’ health data, for example the data from their activity trackers and heart rate monitors.

Social media and health data go hand in hand

People love to share the details of their life, especially when they can brag about their accomplishments.

That’s a basic characteristic of social media and something that is easy to incorporate in a health data platform: ”Today I ran 10 kilometers and burned x calories”. It’s also easy to compete in sports with your friends in social media. And it’s easy to admire or ”like” their accomplishments.

In other words, a whole lot of positive vibes can be created within such a platform.

Aetna’s challenge is that they are an insurance company. And well, insurance companies are not usually associated with events that are fun, right? Besides, there’s always the suspicion that the insurance company might be taking advantage of the data you upload in an app.

Suspicion and fun don’t mix well.

Apple just seems to be a better match with the idea of fun and achievement. Plus you can feel even better about yourself showing off your Apple-designed activity tracker.

This is why Aetna’s decision to pull the plug off CarePass is no indication of Apple not making it. Quite the contrary, I’d say it rather proves that Apple is more likely to come out as a winner in the platform game than any insurance company.

All about wellbeing, design and fun

If Apple unveils the iWatch tomorrow, they are likely to emphasize anything but potentially sharing your health data with insurance companies at some point. It’ll rather be about wellbeing, design and fun.

The same will apply to the other contenders in the platform game. The fight for the most popular health data platform will be an interesting one to observe.

One day we might see Aetna and its competitors partnering with Apple and the likes, encouraging people to lead healthy lives and charging smaller premiums from those who excercise regularly.

Eagerly waiting for tomorrow’s event.

What business are heart rate monitor manufacturers in?

Answer: they are in the health data business.

A startup firm called PulseOn was featured in an article by the leading Finnish business magazine Talouselämä (in Finnish) about a week ago. The company has developed a heart rate monitor without chest belt. I love the invention because I hate to wear a chest belt while working out. 

The article also mentions a number of other Finnish startups that focus on measuring your body, and quite correctly states there’s some unique know-how in mobile and health related technologies in Finland. This is great but not good enough.

The story becomes more interesting when you consider that there’s also excellent competence in data analytics in Finland, and equally noteworthy competence in the healthcare and insurance businesses. 

These are some of the competences that PulseOn and their competitors, such as Polar and Suunto, will need to acquire through partnerships or by hiring new employees.

The reason is simple: the activity trackers and other devices measuring our body are only a small part of the healthcare and health insurance business ecosystem. The US alone is expected to spend 3 trillion dollars in healthcare this year, and the money spent is rising every year. 

Monetizing Data

The everyday health data collected from our bodies will have such a big impact on the society’s healthcare costs that the players controlling the flow and the use of that data will also come to control the activity tracker and heart rate monitor business.

The size of the business opportunity is enticing the big insurance companies into the game, as well as the heavyweights of consumer electronics and the leading companies specialized in analyzing and monetizing data. 

In the face of competition like this, companies like Jawbone, Fitbit, Garmin and their above mentioned Finnish competitors will suffer unless they manage to get well connected into the wider ecosystem and monetize the health data they gather.  

The CEO of the insurance company Aetna put it nicely by saying they are “no longer in the insurance business, but in the information business instead”.

No Competitive Advantage from Technology Alone

A heart rate monitor is hardly such a complex device that any manufacturer would be able to create a sustainable competitive advantage through its technology alone. 

For instance, the July issue of Scientific American shows off filmlike patches of “electronic skin” containing electronic components capable of measuring the body’s motion when integrated with an accelerometer.

I’d expect this is only one of the technological innovations we’ll see becoming commoditized in the health business as time passes.

Enter Incentives by Insurance Companies

The ever-increasing capabilities of gathering quantified-self data will have a tremendous impact on preventing and treating deseases. I’d assume that pretty soon this kind of everyday health data will be gathered from most of us. We already have insurance companies giving people incentives in exchange for their body measurement data. 

An American friend of mine already gets money off his automobile insurance because he’s agreed to have the insurance company install a device into his car monitoring the way he drives.

From the point of view of the insurance company’s business, a device measuring the human body is no different from the device in the car. 

The Bridge that has a Loyalty Program

If you’ve watched the crime drama “The Bridge” on TV, you’ll be familiar with the bridge connecting the Danish capital Copenhagen and the Swedish city of Malmö.(* The CRM and email program of that bridge is surprisingly sophisticated.


More than 20 000 cars cross the Öresund bridge between Denmark and Sweden daily. Most of the bridge users live close by, and about half of the trips are related to leisure travel, the other half being business.

The bridge has nearly 300 000 loyalty program members, carrying a device that allows them to pass the toll booth through a priority lane. This is only one of the benefits they receive.

Increased sales

If each loyalty program member crossed the bridge one additional time each month, the bridge company sales would increase by 60 million euros. Boosting traffic is the aim of the loyalty program. In other words, they want to increase the number of customers and increase their shopping frequency, like in any other loyalty program.

Each member gets profiled according to his or her behavior pattern for using the bridge, and their declared and observed interests for leisure time. Based on the profile, the customer gets personalized communication from the bridge company, whether it’s by email, contact center, website or the mobile app of the bridge.

Does your CRM program have these ten features?

Here’s some of the stuff the Öresund Bridge loyalty program does. Is there something on the list that you could apply in your program?

  1. Customer contacts are tailored based on the customer profile that is unique to each individual. The same message never goes to all customers.
  2. Customer segmentation is based on the customer’s actual and observed behavior – not just on what they claim to be interested in when asked in surveys.
  3. In marketing emails, each click on each link on every email gets registered for each individual customer. This data is stored in the customer analytics and dialogue database. For instance, the customer clicking a link about a golf tour offer is probably interested in golf and will see golf-related offers in the future as well.
  4. The profile -based offers are presented to customers in both outbound and inbound channels. The customer contacting the call center is informed about the current offers most relevant to him or her.
  5. Every email campaign is used for testing different versions of the message. This so-called A/B testing is done in all campaigns. Consequently, there’s continuous learning and improvement in campaign results. The open rate of the personalized emails is impressive, over 30%.
  6. Communications program based on customer life cycle stage. The bridge company takes the customer’s life cycle stage into account in each contact. The stages they use are: Generate =>Develop => Nursing => Winback.
  7. Most of the 1-to-1 messages going to the customers are sent automatically, based on triggers. Automatized communications result in huge savings by reducing manual work and by preventing errors that are typical when creating campaigns manually. The triggers are typically something that the customer did – or didn’t do.
  8. Email addresses that are no more in use (hard bounces) are actively updated by asking the customer to give his or her current email address at every opportunity in the other contact channels. An email address is not less valuable than a postal mail address.
  9. Prospects visiting the web site of the bridge get targeted display-advertising after their visit. Even though the visitor is not yet identified, he or she gets retargeted by behavior-based web ads.
  10. The bridge has a mobile app for their customers. With the app, you can plan your trip, and it also prompts you about current offers. The app can also be used to post the trip on social media.

 Does your loyalty program win the Öresund Bridge?

This loyalty program is a nice example of good use of customer analytics and marketing automation. If your CRM program does all the things listed above – congratulations! If the Bridge beats you, how about your competition then, are you able to beat them in the customer centricity game?

(*The American version of “The Bridge” TV series features a different bridge, namely the one connecting El Paso, Texas, and Ciudad Juarez, Mexico.

Photo credit: Nikos Roussos, licensed under the Creative Commons Attribution-Share Alike 2.0 Generic license.

This is an English version of an article published in the Finnish DMA yearbook. 

Kesko dared, will S-group follow suit?


This fall Finland’s number two retailer Kesko began targeting their direct marketing based on their customers’ purchase history. Doesn’t sound too special, but that’s what it is. They became actually the first brick-and-mortar retailer to do it in this country.

Finnish retailers have been gathering their customers’ purchase data for years. However, from the customer’s point of view, this data has largely been left unused. From here onwards, the customer will hopefully see well executed personalized offers on products they like. In addition, there should be an improvement in customer experience, resulting from improved insight from analyzing the purchase data.

Kesko has thus embarked on a journey paved by Tesco in Britain some 20 years ago. Making use of customer analytics catapulted Tesco to the market leader position in Britain, made it the second largest retailer in the world, and helped it create a sizable ebusiness. According to former CEO Terry Leahy, productivity of Tesco’s marketing improved by 1000% because “offers could be tailored to what people actually wanted to buy”. Simple and smart.

The story of Tesco’s loyalty program can be read in this book that has already become a classic of sorts among marketers interested in customer insight. One of the key messages of the book is that in addition to marketing, actually everything that the company does is guided by the insight they get from customer data.

Finnish retail has finally entered the 1-to-1 marketing era. Kesko dared take the risk and face the criticism of those consumers who have privacy concerns about customer analytics. This sort of hesitation is probably hard to understand in many parts of the world but in this country it’s been the reality so far.

So, will Finns abandon shopping at Kesko stores as a protest? Of course not.

It’ll be interesting to see the response from S-group – the number one retailer – who’s expected to nominate its new CEO tomorrow. One of his key tasks will be to embrace ecommerce, something that Finnish retailers have so far left mostly to foreign competition. And this is starting to hurt.

Hence, this time the logical step for S-group would be to follow on Kesko’s footsteps, as it’s hard to imagine ecommerce without personalized marketing.