You cannot have a conversation about B2B marketing without talking about data. Data is the very lifeblood of any marketing campaign; regardless of the creative, the channel or the execution, if the data isn’t right the campaign will fail.
Which is why it’s so surprising that so many organizations still put their entire marketing campaign at risk by using bad customer data. According to recent research by Royal Mail Data Services, 70% of the 300 companies surveyed admitted to having incomplete or out-of-date customer data. And the problem is getting worse given this figure is up 12% compared to 2014. The cost of this bad data is 6% of annual revenue, although the research states that 34% of marketers fail to fully understand the financial impact of poor quality data. But it’s not just about money. Organizations are risking more than just their bottom line if they use data that is incomplete, old, or low quality.
If 6% of annual revenue is lost because of bad data, then this is only compounded by the additional loss in investment, time and resources that using bad data can bring about. Sales teams invest huge numbers of hours calling or mailing incorrect contacts, a waste of both time and money. Investments in marketing campaigns where only 50% of the emails or direct mailers get through is not uncommon. It is not just a waste of time and money — it is also a waste of resources for the marketing team who collated the campaign and worked on it for little or minimal results.
If you send an incorrect mailer, a direct social post to the wrong person, or your sales team calls an organization and doesn’t know the right person to speak to, then any chance of building trust between you and your potential customer is lost at best. At worst, any existing trust in your brand is destroyed and the damage to your reputation long lasting.
And it’s not just your company’s reputation at stake. Bad insight and data from a marketing campaign yields false or insubstantial numbers of leads for your sales team. There is already a perception that marketing and sales do not collaborate enough when it comes to lead generation, and bad data only accelerates this problem. Incorrect information risks the reputation of the marketing department, but also the reputation of the sales person making that phone call. Sales people trade on their ability to bring in business and their individual reputation can be damaged by having incorrect customer knowledge or contact details.
Organizations spend time and money ensuring their messaging is right; that the tone is correct, the promotion suitable and that central narrative will resonate with the recipient. The desire for increased personalization means messaging has never been so important – customers expect you to know what they are interested in, and tailor messaging accordingly. And yet if the contacts are inaccurate this carefully crafted messaging is ignored and the time and resources spent developing it wasted. It could result in a recipient unsubscribing or at the very least a reduction in trust.
Data pollution risk
One of the challenges with data is how much latent information organizations already have within their walls. Many organizations simply add in some ‘good’ data to their existing CRM or repository and assume that solves the problem – after all, at least they are increasing their chances of getting the right campaign to the right recipient. But once you’ve merged all your good data with some potentially dirty data, how do you start to clean it all up?
The marketing landscape is changing, but the one constant, regardless of channels, customer desires and campaign narratives, is that getting the customer data right is a fundamental basic. And, given the trend for increased personalization in marketing, the heightened competition for customer mindshare, the importance of targeted campaigns such as account-based marketing, and the leads these can generate, the quality of the data you use has never been more important to the success of your entire business.