Imagine if you knew everything about your customers: their interests, who they socialize with, how they buy, what they like, what habits they have, how they are as people and what their needs are. What could you do what that information? You would probably be much better at sending the right message, at the right time, and with the right offer at the right price. This is something that would probably be useful for both parties. As customers we have become increasingly allergic to unnecessary advertising and sales people who call incessantly. It is not effective to communicate generically, widely and broadly. The future belongs, therefore, to companies that begin instead to deliver relevant personalized information based on knowledge about you as a customer. Target shooting instead of mass communication. This has long been a dream for many companies and sales people. But it is no longer only a dream. By analyzing large quantities of data about our customers that they provide digitally, this dream has become more and more realistic.
The trend toward increased personalization is evident in all digital services that have appeared in recent years. Netflix recommends films and television series based on what you have already watched. Spotify generates different types of playlists based on your listening history. Trivago offers trips and hotels based on your travel habits and Facebook ensure that your news flow is filled with pictures of cute puppies. Because – to be honest – you have “liked” pictures of dogs in your feed. Digitalization has made this trend possible, but it is above all customers that drive the trend. For example, over half of all customers in the United States expect companies to anticipate their needs and send relevant offers1 and 84 percent want companies to see them as a person, not as a number in the system.2
Personalization is the automatic tailoring of sites and messages to the individuals viewing them so that we can feel that somewhere there’s a piece of software that loves us for who we are. | David Weinberger, writer and expert in Internet marketing
Personalization can create huge opportunities for companies. Instead of stubbornly offering the same service every time, one can adapt information and key messages depending on who the customer is, where the customer is, where the customer is going, who the customer wants to be and in what condition the customer is. This is particularly interesting from a sales perspective. Increased access to data about position, behavior, etc., creates opportunities for new and exciting applications, where one can individually adapt messages and deals.
With the help of available data we can study people’s behavior instead of their opinions. Data can include information such as location information from a person’s cell phone or information about how a credit card is being used. It shows what people really choose to do, instead of their opinions. By analyzing such data, researchers can make predictions about individual people, such as whether it is likely that they will repay a loan or if they are at risk of contracting diabetes. The perhaps most interesting things occur when several different facts about time and place and a person’s status and ambitions are combined. Many companies invest billions in this. Google, for example, has an expressed ambition to make searching superfluous by delivering search results in advance, in the form of offers – services that can become a natural part of our daily lives, where we receive information exactly when we need it. Imagine a tourist in Paris who loves fish and wants to become a wine expert, but has a limited budget. She can, right there, receive the suggestion: “It is 7pm and you are in Paris. There is a table available at the fish restaurant La Poissonnerie, where they are offering a discounted fish soup for 14 Euro as well as a wine tasting in their cellar afterward for 25 Euro. Would you like a reservation?”
Personalized messages can be extremely complex from a technical perspective, but from a user perspective be tremendously adapted and refined. Netflix is an interesting example. The company has more than 1,000 employees in Silicon Valley that work daily to ensure that their algorithm makes the right film and series recommendations, at the right time, based on the user’s needs and personality.3 And the more the user watches, the better the algorithm becomes. Netflix has an enormous annual budget for this. Their team is comprised of psychologists, sociologists, media experts, and even some philosophers.
The trend towards increased personalization is not just an issue for B2C companies. Not only customers are looking for information and want adapted and timely offers. Personalization is taking off with a vengeance in the B2B world. As professional B2B buyers we want the same assistance. Several studies indicate that B2B buyers want tailored information and personalized experiences for their companies, because they feel that it provides them with valuable decision-making support.4 And even here it seems that more and more companies are deciding that it is ok to release data, as not as it is not abused.
An exciting example of this is a service developed by the company Crystal Knows. The service collects data from thousands of sources on the Internet to find information on a specific person, what is written about her, what she writes about herself, and the digital footprints that she leaves behind in social media. Crystal Knows then performs a personality test of the person, in a matter of seconds. For a sales rep, this means an increased capacity to personalize a message for a potential customer. Crystal Knows, which is also integrated with LinkedIn, suggests how the sales rep should prepare herself, how she should communicate, and which words to use to obtain the best results. But can an algorithm really perform a sensible personality test based on digital footprints? Yes, if we are to believe researchers from Stanford and Cambridge.5 Algorithms perform better personality tests than we humans do.
This technology is even being used in larger commercial contexts. McKinsey has, for example, launched a product called Afiniti based on this technology, which makes personalized customer relations possible. What does it do? Amongst other things, it is used in customer service to match the customer’s personality with the personality of the employee. If, for example, you are a customer with the telecom company T-Mobile and place a call to customer service, you can be matched to the right person who can adapt the conversation based on who you are as a person. The interaction becomes adapted individually. According to T-Mobile this has increased both their profits and customer satisfaction.
On the whole, we can establish that the future belongs to companies that don’t disturb their customers unnecessarily. They base their offers and their communication on data about the customers. The possibilities are understandably large, even if integrity is, in all likelihood, eventually going to become a hotter issue.
1 McGinnis, D. (2016, 2 December). Please Take My Data: Why Consumers Want More Personalized Marketing [Blog post]. Downloaded 2018-10-22 from https://www.salesforce.com/blog/2016/12/consumers-want-more-personalized-marketing.html
2 Salesforce. (2018). Salesforce Research: Customer Expectations Hit All- Time Highs. Downloaded 2018-10-22 from https://www.salesforce.com/research/customer-expectations/
3 O’Reilly, L. (2016, 26 February). Netflix lifted the lid on how the algorithm that recommends you titles to watch actually works [Blog post]. Downloaded 2018-10-22 from https://www.businessinsider.com/how-the-netflix-recommendation-algorithm-works-2016-2?r=US&IR=T
4 Ryan, J. (2017). B2B Personalization: Delivering One-to-One Experiences to Buyers. eMarketer.
5 Parker, C.B. (January 2015). New Stanford research finds computers are better judges of personality than friends and family. Stanford News. Available: https://news.stanford.edu/2015/01/12/personality-computer-knows-011215/