According to a study by HFS Research, 75 percent of business executives do not have a high level of trust in their data. This lack of trust comes despite 89 percent of executives surveyed saying a high level of data quality is critical for success.
This disconnect goes to the heart of trusted data readiness. Trusted data isn’t just complete, accurate or timely – it’s data you can explain, validate, and stand behind. Whether powering AI, personalization, or strategic decisions, trust is essential – the second of the three data readiness pillars related to making data fit-for-purpose. We previously covered data being actionable, and will close out the series with a focus on the importance of data being compliant.
Trusted Data & Actionable Data
We discussed how trust is related to data being actionable – a separate pillar of data readiness. To recap, some data that is made accessible – such as PII or PHI data – has certain rules attached for how it may be accessed and used. Those accessing it must have faith that the appropriate APIs govern its use. The same holds true for synthesized data and other more obscure data types.
Trust and Validation
While having the right APIs in place covers one element of trust, data readiness also requires the validation component. Full data readiness provides users with the ability to verify the dataset and not only see what the quality, completeness and timeliness are but to also see how those components change over time.
Data observability describes the ability to monitor data quality and data pipelines to ensure that data is reliable, trustworthy and compliant. It fast-tracks how marketers, CX professionals and business users of data are able to vet the data they’re working with, without having to rely on IT or data scientists.
The Six Pillars of Data Readiness: Trusted
Data observability yields confidence; whatever the business use case for customer data, having ready access to dashboards that provide a way to interrogate the data allows the user to identify any issues, or determine the source of a bottleneck or other problem. It’s the difference between moving forward confidently vs. having to accept on faith that data is fit-for-purpose.
Maintain Trust Over Time
To ensure completeness and timeliness are monitored over time, data observability dashboards must also provide instance history as another layer of trust, a backstop to track data evolution over time and verify if an anomaly is really an anomaly. For example, if there are an unusual number of customer records in a particular feed, instance history provides an easy way to double-check the accuracy. Users have the ability to seek further confirmation, enhancing trust.
Trust & Tunable Identity Resolution
The ability to monitor changes is also beneficial when changes are intentional, such as with tunable matching for identity resolution. It’s one thing to monitor an anomaly such as an unusual number of customer records, but when a marketer regularly sets different rules for how tight or loose a match should be, the ability to monitor whether the appropriate set of metadata is being used is critical for trusting the results.
For example, a marketer using a household flag should be able to easily identify the household flag across the customer and prospect base, be able to question why a household flag was used for specific groupings, and to fine tune the flag as needed per the desired use case.
When identity resolution is delivered as a black box function, the entire match, merge and identity stitching process is inflexible. Marketers and business users of a unified customer profile have no insight into why records were or were not matched, merged or split – degrading trust.
True data readiness accounts for the enormous volume of metadata that is generated amid constant customer change, e.g., names, household dynamics, addresses, emails, other identifiers and behaviors. Tunability empowers marketers to make sense of constant customer change — and to trust that every CX or AI use case runs on the right data.
Data trust isn’t optional — it’s foundational. When users can verify, monitor, and explain the data they’re working with, they gain the confidence to act boldly and deliver better outcomes.
Want to see what trusted data readiness looks like in action? Visit the Redpoint Data Readiness Hub to connect with an expert or schedule a personalized demo.
