I know that alliteration was hideous – the article is better, though (no intentional alliterations included!). If you’re a long-time shopper or business owner, you’ve likely noticed that the approach various businesses take to client management has changed. In addition to resolving customer issues and queries, businesses are expected to make clients feel individually significant. In short, businesses are expected to ensure that customers don’t feel like "just a number."
The phrase "just a number" has been incorporated into various customer communications. For instance, companies are likely to emphasize both the uniqueness of their clientele and the importance of their individual issues (however small) in order to generate more business and encourage a stronger commercial relationship. This all factors into both creating custom user experiences (like suggesting pages or clothing based on a user’s browsing history, followers or past purchases) so that just about all customer-facing communications represent the assurance that we are "not just a number."
So where does Jetlore factor in? Jetlore’s AI-powered prediction technology works to create custom user profiles based on a user’s behavior and the products and content they express interest in. The result is a presentation of the most relevant content per user across various channels (for instance, relevant figures they can follow on social media, or suggested apparel from their favorite clothing website).
Jetlore’s AI-powered Prediction Platform takes the guesswork out of rule-driven automation and intuition-based marketing, providing the most optimal decision for each unique consumer.
Jetlore uses the stored browsing data from customers’ browsing and purchase history as the substrate for their customer-specific suggestions. They do this by mapping customers’ behavior into what they call "structured predictive attributes" such as size, color, fit, style preferences, brand preferences, and preferred materials. The data is structured using visual representations of which things customers like or dislike and then provided to the retailer. For instance, a customer may search for and purchase sleeveless dresses but almost never purchase or view asymmetrical tops – this helps retailers decide which ads are most relevant to that customer.
According to their website, Jetlore analyzes billions of customer-centric data and product information to create rankings of what they predict is the most relevant content per user. Jetlore also offers Predictive Layouts which allow companies to tailor email, web page, or mobile communications to their customers. Customer profiles are adapted in real time, based on their preferences and recent customer interactions so that the first adverts, products, and services that are marketed to the customer are the ones that are most relevant and helpful to them. These templates support multiple content types and markers can set rules for each targetted customer, such as only showing products that correspond to certain affinities or that are related to recently purchased items.
Using the Predictive Content Dashboard, marketers have access to an interface that allows them to track user data and manage content for email campaigns or web pages. They can use this interface to track user data or to automatically generate content based on users’ interests. For more in-depth information on customers’ needs and preferences, marketers also have access to detailed reports and insights based on the data collected. The insights suggest content that may get companies the most views, clicks, purchases or engagement. This content can be anything from products and sub-categories to promotions. Other business-specific KPIs (key performance indicators) can be explored through this platform, as businesses can track data like page views and click-through rates. The performance data for each product and promotion is structured in a report that analyzes the data using multiple variables. The report can be downloaded so businesses can track their most successful content and demographics over time.
Jetlore has the potential to help companies engage better with customers, offer more relevant products and services and provide better customer service based on the unique profile of each customer. Customers may even be incentivized towards communicating more with companies who seem to view them as individual agents rather than a number, however, in the age of both mass surveillance and mass (social) media, customers may potentially feel as if too much of their data is being collected. There has been a recent push back against social media – specifically, media which projects the lives of ourselves and others as a mass spectacle or online marketing that tracks and follows our services, purchases, and activity so closely that the pair of shorts you looked at last week still come up on your Facebook ads. Gaining the trust of consumers in such an environment will depend on how much customers prefer to have ads and marketing targeted at them specifically, and how transparent companies and search engines are with how they use, track, and store consumer data.
What are your thoughts on this kind of marketing, as either a customer or business owner? Feel free to let us know in the comments.