Every few years, a company will embark on a CRM initiative. The trigger for the initiative might be the arrival of a new sales or marketing manager; or an article someone had read; or a similar initiative launched by a competitor.
Conversations will take place along the following lines:
* Not all customers are created equal;
* We need to deal with our high-value customers in a different way to how we engage with our low-value customers;
* We need to reduce our level of churn;
* We need to craft a proper customer experience; and
* We need value-based customer segmentation.
Right away, the person responsible for driving the CRM initiative (let's call him or her a chief customer officer, or CCO) hits a brick wall.
And this brick wall is made up of data and process issues.
Simply put, to be able to do any kind of customer segmentation, there needs to be comprehensive data on the company's customers. The company needs to know who has bought what, when, how often, when last, where they live, and more.
It would seem a relatively simple business, but more than 90% of large companies will struggle to answer those questions. Here's why:
* Business silos: Banks, for one, remain siloed, and as long as their lines of business run apart from each other, a single view of the customer will remain problematic.
* Intermediaries: Insurers typically deal through brokers or other intermediaries, such as specialist insurers (funeral homes, pet insurance schemes, cycling insurance). In this case, who owns the customer, and who owns the customer data?
* Legal entities: High-value customers are often hidden behind legal entities such as trusts. In such a case, it is impossible to communicate correctly, accurately and consistently with an entire category of high-value customers.
* Tension between IT and marketing: In many cases, IT is highly protective of the data asset, and actively resists the marketing team's attempts to access or beneficiate it.
Someone at board level needs to take ownership of the company's data.
Mervyn Mooi is director of Knowledge Integration Dynamics.
So the CRM initiative dies stillborn until, a few years later, there is another spasmodic attempt to revive it. But the issue must be dealt with, as its impact extends far beyond CRM. Poor-quality data impacts throughout any company, and its resolution is a business imperative.
Here are some recommendations for resolving the perennial data issue:
1. Someone at board level needs to take ownership of the company's data. It is far too critical an issue to remain in the province of IT. Ideally, this person should be the CEO, or have his ear. The consequences of data quality end up in the boardroom, so ownership should reside here too.
2. Operationally, a team should be constituted, which takes overall responsibility for fixing the data, and keeping it fixed. This team should have board representation, be led by a data steward, and include representatives from marketing, sales and the customer care team.
3. The goal should be achievable: so rather than aim for 100% clean, current and accurate data across all customer fields, a company should aim to have a control group 100% accurate across a specified number of fields, and then use that learning and experience to extend data quality across the company.
4. Lay a proper foundation with a data-profiling tool. This is the process of examining the available data and gaining insights, statistics and control over it.
5. Where data is siloed, use an extraction, transformation and loading (ETL) solution to build and obtain a unified view of customers.
6. Wherever possible, incentivise customers to maintain their own data. When people maintain and regularly update their own data, it is far more likely to be accurate. And use every opportunity in engaging with a customer to check data accuracy and currency.
With a data foundation such as this in place, a company will be in a position to begin driving some CRM initiatives - but do note, data quality is a lifelong journey, rather than an intermediate destination.
* Mervyn Mooi is director of Knowledge Integration Dynamics.
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