Every time I am away from LinkedIn for more than 2-3 days I get an innocuous looking message, which runs something like –“You’re getting noticed. See who all have accessed your profile in the last few days.” Invariably it gets me intrigued. Who are these wonderful people who are viewing my profile? [let’s face it – there are 2 types of people in the world. The wonderful kind who want to find about more about us and the other kind who don’t careJ] More often than not I will click on the message, which directly opens the App on my smartphone. Once in, the App not only provides who all have viewed my profile but only ‘how’ they stumbled on my profile and also how I rank in the ‘page views’ etc. Most times I will also review some of the latest updates and content on the App itself. Though I haven’t timed myself I would say I spend about 7-10 minutes on each visit.
Though it sounds simple a lot is actually happening to make me spend those 7 minutes! First I am being ‘prodded’ to view the App. Second once I am in the App is providing ‘personalized’ insights which I may care about and finally it is persuading me (ever so gently!) to delve deeper and spend more time in reviewing the latest content which I might have missed.
LinkedIn has had to combine behavioral engineering, design thinking and big data technology to create this addictive behavior in me [in fact there is evidence to suggest that habit formation and addiction may have a similar path formation in the brain]. Although ‘customer habit formation’ lies at the heart of most successful enterprises, technology companies have the greatest access to the customer data and context have the capability of taking this create unique experience at an individual transaction level.
This is perhaps best understood as a 4 step cyclical process as shown in figure below. 2
In our example the trigger was the enticing message, which induced us to take an action, viz. – open the App. The third step was the critical component of the personalized, contextual insights. Why does it need to be unpredictable? The answer lies in the brains pleasure centers, which are more ‘turned on’ when we experience unpredictable pleasant things compared to expected pleasant events. Finally, I am propelled to investment, which includes maybe responding to an invite, reviewing new content etc.
Analytics can play a critical role in ensuring a more effective ‘hook’ for more customers. The cycle hinges on customer being ensured of a ‘personalized, unpredictable, pleasant reward.’ Analytics can utilize available customer data to create personalized offers based on past sales, demographics and search patterns (for example).
Design is the other cog of this cycle. Organizations need to envisage a ‘Customer Journey Map’, which covers all four aspects covered above. What complicates the situation further is the choice available to the customer in terms of competition, multiple channels, variable interest levels etc. Design thinking can help organizations in designing seamless, intuitive and unique experience for the customer thereby creating a powerful habit forming cycle.
Although the discussion above may seem relevant for technology companies today as we move into the ‘connected economy’ companies are going to access to more and more of the customer data. Think of your utility providers, for example. In the next 5-7 years as ‘smart meters’ get ubiquitous they will be privy to a massive amount of customer usage data. Both B2B and B2C companies will therefore need to invest in enhancing design and embedding analytics into their customer’s processes to ensure greater stickiness and profitability.
Disclaimer: These are the personal opinions of the author and not those of IBM.
 Disclaimer – LinkedIn is purely for illustrative purposes. It is not to suggest that it is in any way superior to competitors.