By Lisa Loftis, Contributor to CMS Wire
Getting customer understanding right not only provides great customer experience (CX), it also gives marketers a leg up on what I see as the big opportunities for CX in 2022. We looked at these opportunities in my 2022 predictions and priorities for marketing and CX. But unlike prediction lists of years past, these focus less on cutting edge technology or innovative new practices and more on a “back to basics” approach — focusing on block and tackle marketing best practices or dealing with hot-topic concerns that we have had plenty of advanced warning about. I categorized these into the acronym TRUE, which stands for:
- Trust and transparency in how marketers collect, use, and protect information.
- Resiliency and innovation in marketing practices to keep up with changing customer demands.
- Understanding customer behaviors, preferences, and sentiment comprehensively and in real-time.
- Ecosystems for martech that provide the integration, automation and speed of reaction needed for agile, hyper-personalized interactions.
Today, I want to take a deep dive into customer understanding.
Peeling Back the Onion on Customer Understanding
CustomerThink defines customer understanding this way: “Customer understanding is all about learning everything you need to know about your customers, i.e., their needs, their pain points, the jobs they are trying to do, etc., and their current experiences in order to deliver the experience they expect going forward.”
Marketers have been struggling to get this right ever since I started my career in technology consulting long ago. We have gone from early banking specific CIF applications (customer information files) in the ’90s, through industry agnostic solutions like the ODS (operational data stores), to the MDMs (master data management) and CDPs (customer data platforms) of today.
Despite the continual search for solutions, customer understanding remains a big issue and is tied very closely to the data. In the Forrester study, When Data Drags You Down (pdf), two of the top five focus areas for marketers were improving the quality of customer data and improving the use of data and analytics. One of the top challenges that marketers said they faced was lack of integration across various data sources. When asked what martech would help them the most, technology that facilitates the data aspect of customer understanding was a significant component. Five of the top 10 desired technologies fell into in this realm:
- Customer data integration across every channel topped the list at 80%.
- Customer data unification was 3rd, at 79%.
- Single source of truth customer reporting and insights 5th at 77%.
- Single view of the customer via advanced identity stitching 6th at 77%.
- Democratized data access for campaigns 10th at 75%.
The Foundational Elements of Attaining Customer Understanding
One standout conclusion from both of these lists is that the predominance of digital activity today is making the customer understanding problem more difficult. Consequently, there are some considerations in addition to what marketers told Forrester that should make customer understanding more attainable in the digital world that is 2022. These include the following:
A comprehensive profile — that includes digital activity. The types of data that marketers told Forrester they needed was an interesting mix of traditional and emerging data including (in order): marketing response and interaction, identity, transaction, demographic, social media content, technology ownership and use, applications, sentiment, and preference. To incorporate digital activity, the profile must be able to join known and unknown digital interactions across all owned properties, provide customer-level digital interaction data for tracking, track and synchronize customer behavior across devices and digital touch points, and combine on-line and off-line data in real-time so that all customer data sources are synchronized (digital, transaction, demographic, account level insights, call center interactions, etc.).
Identity management services are required for dealing with digital activity.They aggregate data views for sessions, anonymous prospects, identifiable traffic and existing customers while updating user ID graphs in real-time as the new data is captured. These should also allow for joining of other first/second/third party data attributes through deterministic matching as well.
Privacy measures should be built into the customer data solution that provide personal identifiable information (PII) free identifiers in the cloud and customizable data collection and transfer processes that comply with regulations such as GDPR and CCPA. Gartner places privacy in its top digital trends for 2022, coining the term privacy-enhancing computation which can include encrypting, splitting or preprocessing sensitive data to allow it to be handled without compromising confidentiality. The firm states this is an important mechanism for sharing data across the ecosystem and posit that by 2025, 60% of large organizations will use one or more privacy-enhancing computation techniques in analytics, business intelligence or cloud computing.
Hybrid data architecture that does not force all customer data to be lifted or shifted into the marketing cloud or customer database will gain in popularity. Streaming data capabilities will replace the traditional lift-and-shift requirement because they can allow easy connection to any chosen data environment, enabling the use of data where it resides — leveraging existing investments, controlling privacy and speeding time to value. Streaming data can also help to detect events as they happen and incorporate that data into relevant, analytics-ready customer profiles. Streaming data can also eliminate digital lag, the time between when someone takes a digital action and when marketers can incorporate that information into profiles, segments, and communications.
Data management capabilities should apply to all data including digital. Another top digital trend from Gartner includes the adoption of a data fabric. Data fabric is designed to help overcome the data silos that continue to plague marketers. It uses built in analytics to read metadata, which allows it to learn what data is being used. Gartner says that the ability of a data fabric to make recommendations for more, different and better data can reduce data management by up to 70%. The firm predicts that by 2024, data fabric deployments will quadruple efficiency in data utilization while cutting human-driven data management tasks in half.
Factoring these considerations into the technology solution for customer data, be it an enterprise marketing suite or a customer data platform, will help facilitate the customer understanding that marketers have been striving for since before I entered the profession some 35 years ago.
Article originally appeared on CMS Wire.
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