Make 2014 the year you clean up your database and reap the rewards.
“Organisations experiencing revenue growth are three times more likely to have clean data. “

Here at Twenty, we believe in the 80 – 20 rule: 80% of results come from 20% of your customers. By tailoring the marketing to those all important few, we maximise profit whilst minimising cost. In other words, we help clients’ zero in to influence behaviour where it counts.

In order to find the valuable 20% for any organisation, you need to look into their customers’ lives. Looking at their spending behaviour, transaction history, geographic, psychographic and demographic information would help to identify them. However, this assumes that their information is up-to-date, accurate, complete, and error-free as possible.

This assumption is false for most data. Data analysts estimate that cleaning, exploring, and sanity-checking the data constitutes roughly 80% of the effort. Your insights will be garbage if the data is garbage, regardless of how mathematically sophisticated your analytics may be.

The financial implication of dirty data is shocking. Recently, Demand Metric conducted a study to understand the link between an organisation’s customer data quality with its revenue growth. A key insight was that organisations experiencing revenue growth are about three times more likely to have clean data than organisations with flat or declining revenue growth.

And the problem of dirty data is widespread. A survey by DemandGen estimated that more than 62% of organisations reliant on marketing/prospect data have this problem. Furthermore, 30% of respondent organisations said that they have no strategy in place to manage data hygiene.

From personal experience in the industry, we deal with dirty data almost every day. The consequences if we don’t resolve the issues inherent in such data are returned mailings due to outdated postal addresses, countless bounce backs from invalid email addresses, and the wastage associated with unnecessary correspondence to customers due to duplicate records.

The costs of using mismanaged data keep increasing the longer an organisation relies on that data. Resolving it, in contrast, will reap major benefits. For one, having clean data would mean less time for the analyst to spend preparing it, meaning less cost to the client.

On the analysis side, dirty data makes it more difficult for us to come up with big ROI leads. We rely on segmentation and modelling to profile which consumer and business customers are part of the 20% – the vital few. However, analysing dirty data will also give spurious and non-profitable leads. For the average company, the DemandGen survey estimated only 30% of generated leads become converted sales. This translates to the company losing 70% in pipeline opportunities and potentially losing millions of dollars if the number of generated leads is huge.

In order to keep your customer data as clean as possible, here are some tips:

1) Standardise your data collection methods

Train your data processing team in how to systematically store the data, use multiple-choice options over free-text fields in surveys, and use identification tags to indicate a unique record.

2) Think quality not quantity

You do not have to acquire a lot of information regarding your customers in order to have profitable insights and promote engagement. Remember, the more data you have, the more effort it requires to keep it clean. Establish a ‘critical data requirement’ identifying the information you need for each customer; benchmark the level of completion for that data, then establish an action plan to bridge the gaps.

3) Update the data regularly

Allow and encourage your customers to update their details if they change, get your staff to check a customer’s details whenever they are in contact with them, and regularly remove or flag obsolete records (especially deceased customers!).

In marketing, data is only as useful as the insights attained from them. Otherwise, they are just piles of big, virtual haystacks without the rewarding needle. By implementing standardised data collection procedures, emphasising quality over quantity and regular customer updates, it becomes more likely for you to discover that valuable 20%. You’ll weight the odds of success in your favour and may even discover a real competitive advantage.

Here’s to cleaning up this year.

 

Further Reading:

Sales & Marketing Data Quality by Demand Metric

Assessing the Impact of Dirty Data on Sales & Marketing Performance by DemandGen

About the author:

Joon Yang is a Data Analyst for Twenty. He joined the agency just over two years ago after completing his masters degree at University of Auckland, majoring in Statistics. With his background in statistical theory and practice, he prepares and analyses data to drive insights for a range of Twenty’s clients to improve their ability to engage with customers in a relevant, timely manner. When he’s not doing the Maths thing, he’s indulging his love of music and photography.