Unified view of the customer: what obstacles should be removed to make it a reality?
According to Gartner’s February 2022 CMO Survey, strengthening customer data collection strategies at all contact points is high on the agenda of marketing departments. One reason: the disappearance of cookies to track customer journeys. Hence the need to get a unified 360-degree view through other means.
Furthermore, according to the Gartner study, less than 40% of marketing departments believe they have the right system in place to track customer data and have consolidated and integrated data from all contact points. Data silos within the enterprise remain an obstacle that a third of respondents want to reduce as soon as possible.
The stakes are high: offering a seamless customer experience at all contact points, encouraging brand relationships, re-purchasing and referrals depends in large part on the ability to access a comprehensive view of customers. Such a 360-degree view enables the implementation of personalized customer journeys, including in an omnichannel relationship that has become the norm today.
Fragmented data, a common impediment to the unified customer view
A recurring problem is the fragmentation of customer data. This is caused by siloed systems between tools, including CRM, the system behind a customer portal and other internal solutions. In addition, IT system migrations within the company, for example in a branch network configuration, increase the amount of duplicate data in the database. This results in access to partial, duplicate and not very usable data.
The lack of quality and standardization of customer data is also a source of fragmentation.This problem occurs, for example, in customer service departments that “inherit” multiple records for the same customer, created at different contact points. If the customer created their account online, then called customer service and sent an email, the system may treat each case as if it were a different customer because of the proximity of the entries – a name entered first in full, then with an initial or typo, for example.
Without a data quality solution that helps you capture and cross-reference this information, it is impossible to obtain a unified view of the customer. This opens the door to confusion, such as mistaking a loyal customer for a newcomer or offering them a product they have already purchased.
Centralizing customer data is not enough
Establishing a UCR (unique customer repository) allows you to centralize customer data and to interconnect the different data sources and their operating systems. The UCR allows you to take better advantage of the application ecosystem.
However, even the best UCR will not be able to deliver a unified view of the customer if it contains duplicates, or even triplicates for a given customer, especially from an omnichannel journey. The approach must therefore be taken a step further and the UCR must become a true Golden Record, in other words, the customer data repository that offers the only “source of truth” for customer profiles. This implies exhaustive, accurate, consolidated customer data.
A data quality solution is then needed to support the UCR in order to identify duplicates and merge information from the same client. The best solutions go beyond exact and fuzzy data matching. They allow the application of deduplication processes that can be configured and executed on demand or in batch processing, and to merge data taking into account a tolerance value based on the proximity of records before execution. The must: the verification of the pre-existence of a customer in the system before any creation of a new record. It is then possible to identify the records closest to the entry to check them, and thus avoid that internal users such as customer service, CRM, and marketing unintentionally create duplicate customer records.
No unified view of the customer without Data Quality!
To provide a unified view of the customer, the data must meet the criteria of Data Quality. It must be complete, validated, accurate, consistent, available and up-to-date. And the challenge is all the more important, since non-quality customer data spreads to the information system solutions!
Also, in parallel with the deduplication and merging of customer information, it is essential to improve and maintain the quality of the data in the database, such as the incoming flows. On the one hand, cleaning the existing data allows for applying the unification rules on reliable and verified data. Valid and reachable emails and phone numbers, accurate and up-to-date postal addresses, and a well-spelled name in a single version are all characteristics that a unification process cannot do without. On the other hand, the incoming flows must be checked to avoid polluting the database, which relies on input assistance, an effective remedy against errors and approximations, and on real-time control of the accuracy of the records.
Data Quality therefore offers a comprehensive response to remove the obstacles to a 360 degree view of customers. It can be concentrated in a single solution, provided that it is sufficiently powerful and complete to cover the quality of data both in the database and in real time at the time of entry, as well as the deduplication and fusion of all customer information according to advanced parameters.
About DQE
Because data quality is essential to customer knowledge and the construction of a lasting relationship, since 2008, DQE has provided its clients with innovative and comprehensive solutions that facilitate the collection of reliable data.
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April 19, 2024
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