5 ways your digital analytics strategy is hindering your customer experience

April 20, 2020

These days, an ever-increasing number of customer interactions are taking place over digital channels and every single digital interaction offers an incredible source of customer intelligence for organizations to tap into.

With every visit, customers leave a valuable trail of digital breadcrumbs. These breadcrumbs give organizations the ability to follow each individual customer journey and each customer’s experience along the way. With every browse, click, like and share your customer creates their own digital footprint. And with their consent, brands can harness this rich source of data to anticipate and deliver on the needs of each individual customer, optimize each customer’s journey, and unlock new competitive value for the organization.

Of course, this data must be treated as personal data and companies should provide comprehensive cookie notices to educate users on how they plan to use their personal data, on an opt-in basis.

But despite many customers still opting-in to share this data, organizations are struggling to tap into this readily available digital intelligence in a meaningful and effective way.

The reason? These five recurring challenges create barriers to unlocking the true value of digital data:

  • Tagging is still the predominant method for digital analytics tools to capture data. Not only is there cost and time involved in creating, testing and deploying these tags, but they need to be constantly updated. Updates are required every time there’s a new area of interest or there are changes to the website. This invariably leads to delays in campaigns, and lost data and opportunities.
  • Many digital analytics solutions focus on visits, page views, clicks and campaign triggers. The data collected is rarely at an individual customer level. This makes it challenging to join digital data up with offline data from CRM or single customer view systems, where data needs to be held at individual customer level.
  • Too many organizations are focused only on behavioral data – what a customer clicked on and what they saw, rather than experiential data. Experiential data could include what a customer didn’t see, what price they were quoted or what products were not in stock. Collecting behavioral data without experiential data often leads to an incomplete or misleading picture of cause and effect.
  • The number of digital channels, technologies and techniques for measuring customer experience within those channels has exploded but the data and insight is held in siloes make it difficult to obtain a joined-up view of the customer experience.
  • By the time data is extracted and analyzed for insights, the customer has already completed their interaction. Organizations are still reporting on the past and unable to use data in real time to impact customer experience ‘in the moment.’

Organizations leading the field in digital intelligence are opting for a single view of individual customer-level behavioral and experiential data across digital channels that can be easily joined up to offline data to gain much deeper insight into the customer journey.

The ability to analyze data at this level of detail is helping these organizations go beyond the “what” and “how” of traditional digital analytics and answer the more valuable “who” and “why” questions. Who are my most and least valuable customers? Why do they behave as they do on my digital properties? What simple changes could I make to alter some of this behavior?

By capturing granular, time-stamped customer-level data from every digital interaction about everywhere your customer went, everything they did and did not do and everything they see and did not see, organizations can optimize their customer experience and create competitive advantage.