Creating Meaningful And Relevant Customer Experiences Using Data Quality

Today’s consumers have high expectations for brands, including expectations for highly personalized experiences – with conditions. For instance, a recent Prosper Insights & Analytics survey shows that over 68 percent of consumers state that they don’t like when advertisers buy their personal data.

Additionally, nearly 3 in 4 consumers (73 percent) have taken steps to protect their online privacy. So how can brands meet high expectations for personalization when consumers are hesitant to share their personal data?

I recently spoke with John Nash, chief marketing and strategy officer at Redpoint Global – a leading software provider helping brands deliver revenue-generating, personalized customer experiences (CX) – to discuss this. Follow along as we dive into the evolution of personalization, consumer sentiments around data privacy and brand communications efforts, and how data quality can enable brands to reduce CX gaps while increasing trust and loyalty.

Gary Drenik: What is the biggest mistake brands make when it comes to customer experience and personalization? How can brands remedy this?

John Nash: A common barrier to delivering a personalized CX is a lack of insights, which is really a data quality issue. This can be due to an entrenched mindset of engaging with customers across siloed channels, and a brand’s inability to converse with customers in real time.

To remedy this, brands must have an accurate and unified view of a customer. Identity resolution resolves a customer identity across all devices, IDs and touchpoints – whether an individual, a household or another entity – and is a key step toward creating a customer “golden record,” or holistic view of the individual.

When this view is updated in real-time and accessible to every application and user, brands can orchestrate the personalized experiences that consumers desire across channels and at every point in the customer journey.

Drenik: Survey results show that consumers are willing to provide access to their data in exchange for better CX. Yet, despite this willingness to share information, consumers continue to experience mistargeted information. Where does this disconnect stem from and how can it be avoided?

Nash: According to a recent Redpoint Global survey, 70% of respondents said they receive mistargeted information at least once a month, with data quality issues causing this disconnect. Brands that lack an updated, real time single view introduce irrelevant communications because they fundamentally misunderstand either who they’re trying to engage with, or how individuals move through a customer journey.

When information is relevant to a customer in the context of their unique journey, there is no disconnect. Rather, that opens the door to the value exchange you mention where customers willingly provide data. Why? Because they know it will be used to provide highly relevant interactions that are consistent across channels.

Drenik: Given the increased need for customer data in personalizing experiences, how can brands satisfy customer expectations around trust and transparency?

Nash: Trust is the other component of the value exchange. Customers will provide personal data in exchange for a more personalized experience, with the caveat that brands are also fully transparent about data collection and how it is used. Ideally, preference management does more than check the compliance box and honor the right to be forgotten with GDPR, CCPA and other regulatory requirements. Building understanding, preferences and trust into each interaction gives brands an opportunity to elevate CXs and differentiate themselves in a competitive market.

Drenik: Should brands be leaning into generational differences among each group’s personalization expectations? If so, what best practices can you share for brands?

Nash: If the goal of identity resolution is to know the customer you’re trying to engage with, generational differences can provide valuable insights into what a customer expects from a brand and how customers perceive themselves.

A clustered audience machine learning model, for example, provides opportunities for further segmentation as it finds commonalities among customers that are potentially far more meaningful than age such as purchasing patterns, post-buying behavior and browsing activity.

Research shows that younger consumers are more open to fully digital experiences. In the recent Prosper Insights & Analytics survey you mentioned earlier, data revealed 21 percent of Gen-Z and nearly 25 percent of Millennials are comparative shopping online more often given the current state of the U.S. economy. Curbside pickup and digital returns are just a few other examples of the contact-less, digital-first options that may appeal to these younger customers. Providing flexibility in how CX is received and letting consumers choose an engagement method is another effective way to honor consumer preferences.

As we look ahead though, new technology that allows brands to segment a market of one will likely lead to fewer brands relying on demographic data alone.

Drenik: Personalization continues to be a popular topic for CX – how has the conversation transformed in recent years, and why should brands care?

Nash: Since identity resolution and real-time personalization are now a matter of course for many companies, CX will be critical for brands to differentiate themselves. The technology now exists to do this at scale, in a way that is possible without having to scale your organization to meet these more granular segments. I always come back to a Harris Poll survey, conducted post-pandemic, where 39% of consumers surveyed said they will not do business with a brand that fails to deliver a personalized experience. It’s too much of a risk not to embrace a data-driven approach.

The challenge now is operational. An organization must align its people and processes around existing capabilities while also rethinking and re-aligning entrenched behaviors. Over-investment in channels and under-investment in orchestration will essentially have to be flipped. Companies need to examine whether there’s friction – either in the experience they’re providing customers, or from a disjointed martech stack.

Drenik: For brands that are behind the curve when it comes to personalization, how can they get started on making some of these changes?

Nash: It starts with having a handle on data quality. By starting with the right foundation, an organization can phase in capabilities over time, moving from a channel-centric to an omnichannel approach and eventually supporting more complex use cases. The goal is to combine a single customer view with real-time decision-making and orchestration capabilities, thereby providing companies with a single point of operational control over data, decisions and interactions.

To a customer this looks like a consistent, personalized omnichannel experience that engenders trust and the sharing of more data, leading to deeper personalization, loyalty and enhanced lifetime value. It’s a closed-loop cycle that perpetually builds off its own success.

Drenik: Thanks, John, for sharing your insights on the crucial role data quality plays in the customer experience.