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Clean Data

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5 Min Read

How Data Refreshing can help organisations identify revenue opportunities

Customer and prospect data can be both an incredibly valuable resource and a liability, depending on its depth, relevance and, critically, timeliness. Organisations have a choice: they can either remain in a stale, static sales environment with manually-gathered data, whenever the sales team can find the time; or, they can hire motivated, engaged sales reps and use fresh, relevant data sets, triggered by the latest events. Which would your business development teams prefer?

Whether companies have invested in CRM or are still reliant on spreadsheets to record customer and prospect data, there is now growing awareness that these static data resources are contributing to sales and marketing failure. In this post GDPR era, James Isilay, CEO, Cognism, outlines three steps to take to transform the value of the data resource.

Overcoming Frustration

Poor quality contact and lead data is one of the most frustrating aspects of any B2B outbound sales campaign. Every salesperson has endured the annoyance of time wasted trying to contact people who no longer work for a company; but how many have also considered that an opportunity could be missed if these individuals are not then targeted in a new organisation and role?

B2B contact data is continually changing, and few firms have a robust process in place for ensuring that data is up to date. Even if it is held within a CRM, rather than located on multiple spreadsheets, traditional manual processes for ensuring data is accurate and real-time are simply too resource intensive. Add in the new GDPR pressures of data privacy compliance, and there is a very real risk that companies will not only fail to exploit the value of data resources, they may back away from outreach all together, which would be a huge waste.

So, what steps should be taken to ensure data resources are both valuable and valued?

1. GDPR Compliance & Data Confidence

 

A sales team with no confidence in the quality of data might as well not bother to turn up. From fear of complaint to the looming threat of regulatory fine, a company reliant on out of date, potentially non-compliant prospect data has essentially shut down the sales process. A GDPR compliant data source is absolutely essential for any outreach activity. Whether the business is using internal data resources or an external data provider, proven compliance processes are essential – from correct data sourcing to privacy impact assessments.

2. Data Freshness & Sales Effectiveness

 

Data is always in motion – from job changes to company acquisition – and as a result, the quality and accuracy of data resources continually decays. On the downside, approximately one-third of data degrades every year and most sales teams are using data that is up to 60% out of date – an incredibly frustrating state of affairs. On the plus side, however, data change can also represent an opportunity.  An existing customer moving to another company could champion your product/service and become a great new sales opportunity. The key, therefore, is not only to ensure data is continually refreshed but to also track and acknowledge data changes that could represent potential sales triggers.

While manual data refresh processes are both time-consuming and inefficient, the latest Revenue AI technology can be used to seek out and target stale data in real-time. Revenue AI maps common fields and identifying business profiles, ensuring that B2B companies are dealing with current and accurate CRM data. Whenever bad or outdated records are discovered, a seamless blend of AI and human intelligence delivers an accurate and up to date database of hundreds of million profiles, transforming the quality of the sales experience.

3. Data Breadth & Market Understanding

 

Sales teams have relied on two-dimensional data for too long. Contact name and brief company information provide none of the additional insight required to better understand the total addressable market or prioritise outreach activity. Combining revenue driven AI with a data resource that includes multi-dimensional data, from individual skill sets to education, funding rounds, even technologies in use, can transform the sales process. By creating an intelligence-led sales model that leverages specific purchase triggers and decision making personas to prioritise activity, the sales team can immediately deliver significant bottom-line improvements.

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Start Your Business April 26, 2019
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