From data overload to profit: Making insights actionable

With multiple customer touchpoints in the digital world organisations are becoming inundated with customer data – particularly first-party data.

An increasing number are leveraging AI to make sense of this data and use it to personalise communications, upsell and deliver a standout customer experience.

Yet the quality of this data is often not as good as it should be, with 67 per cent of organisations in a recent study stating that they don't trust their data used for decision making.

We have found that 20 per cent of addresses entered online contain errors, including spelling mistakes, incorrect house numbers and invalid postcodes, often caused by fat finger syndrome, usually due to people inputting data via a small screen. Additionally, data quality declines rapidly with customer contact data lacking regular intervention degrading at 25 per cent a year as people move home, die and get divorced.

Delivering data quality is key for actionable insight

For customer data to provide actionable insight it must be accurate, with access to inaccurate customer data leading to poor decision making. For example, giving an AI tool access to poor quality data on customers could lead to AI 'hallucinations' which results in gibberish, or worse, biased and inaccurate outcomes.

To obtain contact data quality it's essential that organisations have data verification processes in place at the point of data capture, and when cleaning held data in batch. This typically entails simple and cost-effective changes to their data quality process.

Address lookup or autocomplete

At the customer onboarding stage an address lookup or autocomplete service works well. These tools automatically provide the correct address as the customer starts to enter theirs, allowing them to choose an option that is accurate, easily recognisable, and correctly formatted for their country location. This avoids the issue of mistakes caused by fat finger syndrome, and there's a reduction in the number of keystrokes required when typing an address by up to 81 per cent. This speeds up the path to checkout, helping to deliver a standout customer journey. Similar technology enables real time verification of email and phone data at first contact, strengthening critical datasets and enhancing actionable insight generation.

Dedupe databases

Data duplication rates are a significant issue with many retailers experiencing 10 to 30 per cent on their databases. This has a negative impact on effective insight generation.

It often occurs when errors in contact data collection take place at different touchpoints, when two departments merge their data and after a business acquisition when customer data is amalgamated.

Obtaining an advanced fuzzy matching tool can help remove duplicate data. Such a service can merge and purge the most challenging records and create a 'single user record', which delivers an optimum single customer view (SCV) that organisations can make learnings from.

Undertake data suppression or cleansing

Data suppression or data cleansing is a vital component of the data cleaning process, and therefore in supporting efforts with generating insight, because these services highlight those customers who have moved or are no longer at the address on file. A key part of this requires having access to the National Change of Address (NCOA) database that's available in the UK and US, and some other countries, because it highlights those who have moved, and provides their new address.

In addition to removing incorrect addresses, these services can include deceased flagging to prevent mail and other communications from being sent to people who have passed away, which causes distress to their friends and relatives, damaging their reputation, while also wasting money.

By adopting suppression strategies organisations can cut costs, maintain trust, combat fraud, and provide actionable insight.

Investigate a data cleaning SaaS platform

It has never been easier to deliver data quality in real time. A scalable data cleaning SaaS platform that requires no coding, integration or extensive training to use can be deployed within hours as a standalone solution. This technology can clean and standardise names, addresses, email addresses, and phone numbers globally using authoritative data from government agencies, credit bureaus, and utility providers. It can process both newly collected data in real time and existing stored data in batch on-premise. This platform is available not only as a SaaS solution, but also via a cloud-based API and connector technologies such as Microsoft Dynamics and Salesforce.

In summary

Today, it's all very well having access to a large amount of customer data, but it's essentially worthless or even potentially damaging unless it's accurate. Only with quality customer data is it possible improve decision making, because it helps to deliver actionable insight that drives profitability.