The Customer Journey Data Dilemma: Real-Time Versus Historical Data
Purchases, location, and actual customer behaviors are critically important for understanding and mapping the customer experience using the Customer Journey Data.
Despite the increased regulation of customer data collection by initiatives such as GDPR, customers still expect brands to provide a personalized experience that can only be achieved using their data.
In fact, a recent poll found that 53 percent of U.S. adults are willing to share their personal data with brands that use the data to provide personalization and better experiences. With consumers showing the desire to give marketers access to data in return for a better customer experience, companies should be analyzing customer data and using relevant insights to build more personalized customer journeys that lead to better experiences.
As brands shift their focus to become more customer-centric, it’s more important than ever to provide a good experience. Today, 89 percent of companies are competing mostly on the basis of customer experience. Brands such as Amazon, Netflix and Starbucks are regularly recognized for providing outstanding customer experience, so it’s no surprise that these companies consistently exceed customer expectations by leveraging the data at their disposal. The rest of the business world is struggling to keep up – a 2017 report found that 95 percent of companies are unable to make sense of customer data – so marketers must understand in which case each type of customer data – historical and real-time – is best used, how to avoid relying on a singular type and how to most effectively leverage them in combination.
Traditionally, marketers have used historical customer data – past purchases, returns and store visits – as the basis for their personalization tactics. Static data such as customer demographics (e.g. gender or age) are also used in an initial analysis to determine trends among customers.
Purchases, location, and actual customer behaviors are critically important for understanding and mapping the customer experience. Unfortunately, most organizations find this difficult to achieve because their historical data is siloed throughout the business, and therefore, hard to connect. This usually means that these historical views of customer behavior are full of holes.
Marketers should avoid relying solely on historical data as it often fails to encompass changing preferences and current customer behaviors. For example, location data may become irrelevant if a customer changes addresses, and past purchase data can’t always account for evolving consumer tastes. Also, a customer who previously preferred marketing outreach through email may now prefer contact by text message.
However, the most important reason that brands must supplement their historical data with up-to-the-second customer data is to best support the customer experience, which is, in its fundamental nature, a real-time need. This need has become critical in recent years as the empowered consumer has begun interacting with businesses in a different and now real-time way. Smartphones, websites, chatbots, and social channels all deliver an instant response to every customer, on multiple potentially-disconnected channels – brands need to understand the immediate need and desire of the customer to get the response right – and the insight into this is in the real-time data, and usually not found in historical files.
Comprehensive analytics that allows brands to clearly understand customer behavior at the moment is important to leverage this data successfully.
Marketers are therefore catching on to the utility of real-time data, which reports customer behavior at the moment, such as location or engagement with content or ads, but many are struggling to figure out how to analyze and use it effectively.
In fact, 84 percent of CX decision-makers said access to real-time data is important, but only 38 percent have made it a top priority to improve their decisions that affect CX. Real-time data is often overwhelmingly detailed, so comprehensive analytics that allows brands to clearly understand customer behavior at the moment is important to leverage this data successfully.
One place to begin is by actioning purchase data in real-time. If a customer completes a purchase, a company can use this real-time data to immediately share a reward toward a future purchase, creating a personal, positive interaction and laying the groundwork for that person to become a repeat customer.
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Not only can real-time data create a positive customer experience — It can also prevent a negative one. By employing the same real-time purchase data, brands can avoid serving customers ads for products they may have bought only moments ago. Even for customers who have had a negative experience, using real-time data to recognize the customer complaint and avoid targeting the customer with any ads relating to the complaint can help avoid escalation.
Once brands have the ability to action basic real-time data, the next step to optimizing the customer experience is to combine real-time and historical data to create better customer journeys. Marketers can map the initial journey using recent historical data and then use real-time analysis tools to optimize and automate the actioning of data across channels according to determined triggers. A customer journey created by leveraging the two may use historical purchase data to recognize which location customer shops at most frequently, and action real-time location data to provide them with a personalized reward upon arrival at the store.
It’s more important than ever for marketers to reach customers at different stages, across channels, within the time frame that matters to them – instantly. Brands must use all of the data they have at their disposal or risk falling behind in the race towards the best customer experience.