The State of Data-Driven Marketing: A Look at Data Strategies and Best Practice to Fuel ROI

The State of Data-Driven Marketing: A Look at Data Strategies and Best Practice to Fuel ROI

The State of Data-Driven Marketing: A Look at Data Strategies and Best Practice to Fuel ROI
Data is the cornerstone of any successful marketing strategy. Data tells us who are customers and prospects are, how to personalize the customer experience, which channels they prefer, and informs every touchpoint along the customer journey. Despite the importance of utilizing high quality data to fuel new revenue streams and ROI, marketers continue to see data quality as somewhat of an abstract concept. After all, it is difficult to measure, challenging to prove the benefits of investing in data quality measures, and often seen as a time intensive project for which there is no budget.

Whether or not we are paying attention, poor quality data still exists and will continue to undermine even the best laid out marketing strategies. We have all heard of GIGO (Garbage In, Garbage Out), so what we may not be aware of may be causing some serious damage in lost revenue, damaged customer relationships, wasted marketing expenses, and any number of lost opportunities.

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In a report commissioned by Blazent, fewer than half (40%) of the study’s respondents were very confident in the state of their organization’s data quality. Only 50% of respondents believed that the quality of their organization’s data was either slightly better than satisfactory or at least good enough in general.

Industry standards place data decay at an average of 2% per month so over time, the data sitting in your systems will go bad as customers move, change phone numbers, get divorced or married, and so forth.  Beyond this natural decay of data, respondents to the Blazent survey indicated that data entry by employees was one of the most critical sources of poor data quality at 57.5%. Other causes of poor data quality included data migration or conversion projects (47%), mixed entries by multiple uses (44%), and changes to source systems (43.5%).

For those respondents that have implemented data quality measures, the business value proved to be significant. Findings included:

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Informatica, in partnership with Dun & Bradstreet, engaged Ascend2 to conduct a survey on the state of data-driven marketing, how marketers are using data, and their challenges to success.  The Data-Driven Marketing Trends Report findings show data quality as the most challenging obstacle to data-driven success.

Personalizing the customer experience was cited by 58% of survey participants as a key objective for data-driven marketing. Other important objectives included targeting individual market segments (50%), measuring data-driven ROI (49%), and acquiring new customers (41%).

Today’s customers interact and engage with brands on the go, through multiple channels, and at the time of their choosing.

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