Company executives in a variety of industries have found themselves thinking about a single issue: how to create a better user experience by delivering the right offer (or right message) at the right time.
In order to find an answer to that issue, we need to understand the entire journey of a customer across multiple touchpoints both online and off-line. It’s not enough knowing how the customer interacts within a website. You also have to know how the customer responds to emails and how they respond to any off-line touchpoints (such as customer support calls or marketing postcards). Knowing the details of the complete journey will give businesses information they need for better personalisation and that will allow them to use machine learning to analyse the journey and deliver an individualised experience.
Nine in ten marketers say data is their most underutilised asset. Why aren’t they deriving more value from the terabytes of information they collect? Primarily, it’s because that data isn’t immediately usable. Information compiled from varied sources-like websites, emails, sales, third-party vendors and even off-line channels-tends to be siloed and structured in different formats. Even when one department within a firm gets relevant data into a format it can understand, the resulting intel is still largely unintelligible to other teams and departments. If all that data were translated into a single language-one that is equally useful and informative to sales representatives, IT departments, social-media marketers and customer service reps-companies could offer customers more compelling, personalised experiences in real time.
Adobe’s Experience Data Model (XDM) is a formal specification used to describe this journey of experiences, as well as the resulting actions and events. XDM describes not only the journey, but also the measurement, content offers and other details of the journey. XDM is more than just a “data dictionary” for companies working with data from customer experiences-it’s a complete language for the experience business. XDM has been developed by Adobe as a way to make experience data easier to interpret and to share.
The data explosion
Companies have been chasing the real-time customer profile. The biggest problem is that every bit of data seems to be in a different format or on a different platform. You have your website, your email offers, your customer support system, your retail store and a rewards card, not to mention your search, display, social and video advertising across the web. Many of the systems you use to track those items don’t talk to each other or even store the information in a format the other systems can use.
Since you want to use machine learning to derive insights and intelligence from the data and then use those insights to drive company actions, those separate systems make getting a better view of your customer a difficult and time-consuming task. How can you talk about delivering a personalised experience for your customers if every system has a different definition of who the customer is?
To make all these disparate datasets work together and be understood, Data Engineers and Data Scientists are in a constant process of translating and re-translating the data at every step. A large amount of that time is spent understanding the structure of the data before they can turn the data into something meaningful that you can use to create a better experience for your customers.
But streamlining that data is easier said than done. Almost 40 per cent of advertisers employ three or more data management platforms and 44 per cent use three or more analytics platforms. By juggling multiple different data platforms, companies are more likely drop sales leads.
Data flowing in from a company’s smartphone app, for instance, might be in a completely different language than the data acquired from an email marketing campaign, a third-party vendor or from the point of sale. The average data scientist spends about 80 per cent of their day preparing raw data for analysis, according to a recent poll from data mining company CrowdFlower.
Every hour spent cleaning and structuring data is time that could be better spent drawing useful insights from that data, so companies can devise engaging customer experiences.
Imagine if sales and marketing data existed in a single, standardised language from the moment it’s compiled-the same way Adobe standardised PDF for documents.