How Marketers Should Solve Their Data Quality Problems

How Marketers Should Solve Their Data Quality Problems

Posted Monday, March 24th, 2014
Posted in: News

How Marketers Should Solve Their Data Quality Problems

According to John M Coe, the success of direct marketing is extremely dependent on data quality. He states that between 50 and 75 per cent of a campaign’s success rests on the integrity of the data in the contact database. The implication is clear: without good quality data, marketers are fighting a losing battle, and return on investment (ROI) will suffer as a result.

In this paper, we will discuss the risks of decaying data and the challenge marketers face when data does not support their objectives. It’s important to identify data quality issues before they become chronic, and the business must work as a unit to support the marketing department as it strives to retain customers and recruit new business.

Introduction

In business, it’s generally accepted that it’s far cheaper to retain a good customer than recruit a new customer. The cost estimate for new customer acquisition varies, but according to a report from the Chartered Institute of Marketing, a new customer is ten times more expensive. (Some sources in their paper cite the cost as being three times that.)

Businesses retain customers by striking up relationships, maintaining high standards of service, creating loyalty schemes and understanding what customers want. Efficient two-way communication is key. The marketing department must have access to accurate contact details, supported be demographic data that’s up-to-date, and this data needs to be held in a database or CRM system in accordance with data protection legislation.

Marketers simply cannot engage with customers effectively without good quality data. In addition, the marketing department cannot be expected to manage data quality on its own. In many organisations, customer data is used by many different functions; in fact, multiple touch points are a fundamental component of the single customer view.

In this paper, we will look at the challenges marketers face in an age of decaying data, and how the marketing team – and the business – can resolve these data quality challenges.

Marketing data quality diagram

The Problem: Decaying Data

Customer contact details decay rapidly in a database. In 2001, Target Marketing magazine surveyed 1,025 businesses about changes in their

contact databases over a 12-month period. It found that a change occurred in almost 71 per cent of those records. Clearly this is a hindrance to communication.

In 2013, NetProspex found that the average business contact database is 25 per cent inaccurate. It says a decay rate of 2 per cent per month is not unusual. If data is decaying this quickly, a large number of existing customers are not receiving marketing messages; they cannot be retained, and they will be lost.

In business, this also affects the marketer’s budget. All of those out of date records result in waste; wasted resource, wasted effort, wasted money, wasted paper. Without clean data, business simply cannot target their marketing message at the right people, so there is waste here too. It follows that, as the database grows, it will decay more quickly, since there are more customers changing their information, more touch points with customers, more staff interactions and more potential for mistakes.

Dirty data has implications for the brand and its message. At the beginning of this paper, we talked about saving money by retaining customers. If your data about those customers decays, you cannot expect them to be happy about it. If they move home, or start to receive duplicate catalogues, or notice that their maiden name is still on the label, the customer will start to lose the connection to the brand. ROI suffers. Trust begins to evaporate.

The best, most compelling piece of direct mail cannot achieve satisfactory conversion rates if it has been sent to the wrong person, or a person who is irritated by its mere existence.

According to Demand Metric, a marketing research company, 55 per cent of its survey respondents had taken no formal action to improve data quality.

Data Quality: the Marketer’s Solutions

So far, have identified three distinct problems for marketers.

  • Data decays quickly without attention, and it cannot be trusted to maintain its integrity long term. Therefore:
  • Poor quality data results in poor ROI during marketing campaigns, and:
  • Poor quality data results in irritation, inconvenience, and fewer retained customers.

The only possible solution is a concerted, long-term data quality drive that tackles the root cause of data decay, therefore providing marketers with trustworthy contact information that assists them rather than making life more difficult.

So how is this achieved? Naturally, we cannot stop customers from moving house, getting married or changing their names, and we cannot expect families of the deceased to notify every agency that the person ever dealt with. It is therefore down to the whole business (not just the marketers) to implement a three step attack on data decay.

  1. The business must examine how data is captured. It must look at its processes, staff training, software and other variables to prevent data quality problems when the record is initially created. One example is to automatically scan the database for duplicates. Using sophisticated algorithms and phonetic matching, employees can be alerted of possible duplicates and/or invalid data at the point of entry.
  2. The business must proactively scan through its customer records and check them for mistakes and changes. Data quality software is used to automatically scan the database, identify problems and resolve them. Flaws can be presented to a human administrator for verification to ensure there are no mistakes, and the data quality software can use third party information – such as postcode checkers – to ensure the data is correct. It is also possible to scan the database against records of people who have ‘gone away’ – moved to a different address.
  3. There must be an ongoing data quality initiative that protects the database from decay from day to day, or week to week. In other words, data quality should be considered a continual work in progress, and the business’ resource allocation should reflect this.

DQ Global

DQ Global has developed a range of data quality products for businesses. It has supported many large brands in realising data quality goals, including 3M, Toshiba and Harvey Nichols.

Several DQ Global customers were specifically interested in improving data quality for marketing purposes; Harvey Nichols, for example, used DQ Global’s data quality software to implement a single customer view, enabling marketing teams to segment and target customers more effectively, and cutting down on the amount of wasted effort.

Using a combination of proven data quality techniques and unique technologies, DQ Global’s range of data quality software supports all three of the identified solutions above.

  1. Improving your data capture processes: DQ Components is DQ Global’s API. Developers can use it to add DQ Global’s data quality expertise to practically any application they develop. It checks that data is held in the correct format, checks for phonetic matches, compares records, derives demographic data from contact details and much, much more.
  2. Making data correction simple: DQ Global® has produced Match™, a deduplication and cross matching software application that scans customer databases for potential duplicate records. DQ Match™ is a versatile tool that can be used with practically any database or CRM system. DedupeExpress™ is a lighter version of DQ Match.
  3. Supporting ongoing data quality initiatives: DQ Global’s application stack can be used across your organisation. DQ Studio™ supports data quality initiatives in every department and hooks in to a range of common office applications, and DQ Global also produces various solutions that hook directly into popular CRM tools, including Microsoft Dynamics CRM and Saleslogix CRM.

The solutions are efficient, usable and affordable, and all of them allow the business to keep their data in house, making the security unbeatable. All of DQ Global’s data quality tools help businesses to improve their marketing ROI, improve customer satisfaction and reduce waste.

Where user intervention is required, the tools integrate directly with the application and use simple interfaces that require virtually no training. Data quality is not simply a marketing problem, but DQ Global’s easy to use software ensures that the marketing department can take ownership of the solution without undue costs or delays.

Customer testimonials for all DQ Global® products are available on the DQ Global website.

Summary

Tackling data quality is not simple for any business, particularly one that is growing quickly. If data decay becomes endemic, the marketing department will find itself unable to respond efficiently or make reliable predictions about its campaigns. Over time, the brand loses credibility and the customer suffers. If data quality is allowed to drop further, the business will start to see an effect on its profits.

For the best chance of raising data quality, marketers need the backing of the whole business, and they must have buy-in from decision makers higher up the chain. Only then can a business work as a unit to solve marketers’ data quality problems.

Are you ready to tackle your data quality problem? Click here to read more about DQ Global’s data quality software solutions.

Written by

Martin is CEO and founder of DQ Global, a Data Quality Software company based in the UK. With an engineering background, Martin previously ran a CRM Software business. He has gained a wealth of knowledge and experience over the years and has established himself as a Data Quality Improvement Evangelist and an industry expert.
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