How to move away from reactive to real-time customer experiences
Better customer experiences mean better brands. We know that up to 70% of customers will turn their back on a business after just one bad experience. We also know that experience-driven businesses grow revenue 1.4 times faster than others. Despite this, 69% of businesses aren’t embracing CX best practices, meaning now is the time for disruptors to reap the rewards of winning the experience race.
So, how can you win that race? By going real-time, right away.
What does real-time customer experience mean?
Marketers know their customers don’t want an out-of-the-box experience. So brands are gathering data to drive personalisation and build more tailored experiences centred around the customers.
But there’s a difference between using a static store of historic customer data to predict what users want — and architecting that experience according to user interaction at any moment, within any arm of your business.
Many organizations fail to reach this stage due to a classic tunnel-vision approach: they simply fail to join the dots between their lines of business.
One example could be a roadblock between customer service and sales that results in irrelevant communication about a product that isn’t appropriate for the customer. Alternatively, it could mean a siloed data structure that stops offline data from traveling with a customer to an online store, leading to a customer being offered a promotion on an item they’ve already purchased.
Eliminating the disconnect between lines of business and their data streams is a serious cultural and technical feat. Here’s how to make the most of your data infrastructure to meet this challenge.
How to create real-time customer experiences from your data infrastructure?
1.1 Build a central data foundation
The issue: Brands use multiple systems to gather large amounts of CX data such as third-party vendors, offline channels, social media, websites, or transactions. The problem here is that most systems have their own standard semantic data modes so, even within public clouds and data lakes designed to manage and store CX data, they can’t be centralized or democratized.
In other words, each data set has its own language so they simply aren’t able to speak to each other. That makes this data largely useless to siloes which use different data systems, meaning it ends up being unused: a waste of valuable time, ROI and insights.
The answer: Businesses need to build a single data foundation that stores all CX data in a single language and in a single place. Adobe Experience Platform is an extremely effective solution for this since it also integrates with non-Adobe systems.
A central data foundation widens the horizons of the data which each line of business can access - enabling them to deliver more coherent customer experiences, in real-time and at scale.
1.2. Stitch together a supreme view of customers
The issue: Many businesses’ data infrastructure simply isn’t designed to provide a single view of the customer that stitches together many different data sets into one actionable profile.
For example, a brand might have access to high volumes of customer attribute data (the characteristics that rarely change, like users’ gender, marital status, or date of birth). They might also have gathered a large amount of behavioral data (the constantly evolving interactions they have with the organization, like changing their membership status, returning an item, or contacting customer service).
However - many brands lack the ability to rapidly weave together these two types of information and truly bring their customers into focus and then act on that insight in real-time.
The answer: Adobe Experience Platform, XDM (Experience Data Model) builds a standard data language that makes customer data just as useful for every line of business. Data from offline interactions, online journeys or customer attributes can be democratized into a single source of truth and a living customer profile that’s constantly being updated.
Adobe Experience Platform can dynamically create customer profiles by stitching profile fragments within sub-second timeframes, and at scale too. That means instead of constantly translating and interpreting data to make it usable, businesses can work on putting that customer profiling to use in customized experiences.
1.3. Reduce time lag
The issue: We’ve discussed how roadblocks between lines of business make data less useful and prevent brands from piecing together a clear and detailed view of their customers. Finally, there’s the time lag involved.
Often, different lines of business use disjointed applications and data lakes that create a time lag when it comes to sharing that data across different points in the customer journey. To transport that data, it needs to be unified, connectors need to be built, semantics need to be standardized, and all that takes time. The process is time-consuming and means experiences become reactive rather than real-time.
The answer: Reducing and simplifying data workflows is a crucial step, such as by consolidating operational and analytics data systems. Operational systems unlock instant access to profile data such as on a mobile app that needs to make decisions in milliseconds, whilst analytics systems might sift through huge data sets to train machine learning models or find patterns.
Historically, these run on two separate systems with two different workflows. But solutions like Adobe Experience Platform can fold these workflows into one in a symbiotic relationship that enriches profiles and feeds analytics at the same time. This reduces complexity, ROI and latency, all in one go.
Going real-time, right away
Less than a third of businesses are experience-driven. Brands today have a unique opportunity to lead and disrupt by prioritizing the ability to build their experiences in real-time, rather than reactively.