Merging Service Providers
Missing aspects: Open-minded culture, Robust and clean data, Explored customer needs
Two service providers went through a merger and began looking for synergies straight away. As a business objective, they wanted to increase revenue by targeting and reaching each other’s customers. They implemented a rushed communication campaign and tried to provide appealing offers but didn’t realize that they’d had raw, unrefined data about their customers’ needs and interests. Offers were dispatched to the wrong segments, some customers received the same offer over and over again, which ruined personalization.
Their personalized eDM campaigns eventually failed due to low conversion rates and bad CX.
Digital Content Provider
Missing aspects: Future-proof infrastructure, Robust and clean data, Explored customer needs
The company sought to launch a new app and was very confident about its understanding of personalization. They were fully focused on creating a shiny frontend for the app but didn’t do much with the spaghetti architecture in the back. A jumbled IT stack makes the use of data in personalization schemes difficult and overcomplicates processes of measuring and monitoring results and KPIs. Furthermore, as customer needs were not explored, the company failed to realize that their users were more interested in the quantity of content than how it was presented through recommendations.
In the end, the management seemed doubtful if the new app would deliver the financial results they’d hoped for.
Financial Service Provider
Missing aspects: Future-proof infrastructure, Robust and clean data
A mammoth financial service provider wanted to increase operational efficiency by moving all its data to digital channels, as it was struggling with its legacy systems that also severely limited customer options. They intended to launch digital self-care solutions which required the presentation of personalized information, however, due to technological debt incurred through said legacy systems, it led to a host of issues, including cases where customers found misleading or incorrect data about services (e.g. billing). The company meant well, but its systems were so obsolete that it made the smooth transition to digitally personalized solutions all but impossible. Instead, they should have started the process with data cleansing; using data virtualization tools that could bundle up all the fragmented data and organize it, which wouldn’t be a huge investment when done smartly.
Physical Industry (Agriculture)
Missing aspects: Open-minded culture, Robust and clean data, Explored customer needs
Slowly, most companies in physical operations are starting to realize they generate enormous amounts of data that can be utilized in their sales processes. Such was the case with a company dealing in agricultural products; at first, they didn’t want to understand that personalization could help their efforts. They knew they had the data and sought to provide a digital solution with great UI but overlooked that they could take it a step further, see what their customers are doing, and tailor the solution to their needs. In this case, by processing data about generations of seeds, soil composition, weather, and more, then comparing such patterns to data gathered from the fields of neighbouring farmers, they could help their customers pick the best seed, soil, equipment, and agricultural technique that best suits their unique circumstances.
Data can be easily applied to digital surfaces for differentiating experiences , so prototyping with real data can help in these situations to get a better grasp on customer needs.