A faster path to ‘Yes’: using engagement science to move prospects to customers

Digital marketing platforms and social media have enabled speed-to-market to increase dramatically in every tech market, with prospects moving in and out of the sales cycle more quickly than ever. This presents both an opportunity and a challenge for companies and their sales and marketing teams who are trying to get in front of prospects on a timely basis, make their case and close the sale.

The answer is to increase the velocity of the sales cycle and take a lead over competitors. How? By combining account-based data, predictive analysis and content assets – on demand – a process of engagement science.

Engagement science: combining account data with predictive analytics

Data driven sales and marketing intelligence make prospect and customer databases a norm for every enterprise. While sophistication of databases may vary, they typically include contact information, contact preferences and perhaps some transactional data. The data is usually created using a combination of internal and external data sources – and its timeliness and accuracy should regularly be validated. It’s all very necessary – but in today’s hyper-competitive environment, this basic data, even when accurate, just doesn’t go far enough.

Analytics can help identify the right accounts, and the right contacts in those accounts, to begin engagement. When combined with sales and marketing data, newer forms of predictive analytics can help facilitate a deeper account understanding by allowing companies to identify prospects that are in the market to buy.

Using phone-verified and scored account intelligence aligned to a particular category of interest, data can provide signals such as purchase likelihood, current technology utilisation, specific technology budget, behavioural data and more that can be applied to find just the right account-based prospects and influencers to fill the sales pipeline with qualified leads.

According to Aberdeen Group research, companies that prioritise a diversity of data in sales and marketing systems enjoy more than double the organic revenue growth and six times the increase in operating profit over companies that use more traditional data sources – Data Diversity and Cutting Edge Insight for Sales and Marketing, August 2016. Such data sources go beyond compiled business data and firmographic information to include social and web-posted insights, in-market buying triggers, company product announcements and investor intelligence and vertical market trends.

This increase in data diversity can help drive significantly more value in account intelligence than seen in a more traditional data environment. For instance, predictive data can help pinpoint triggers that might include finding a VP of marketing at a health care company that uses Cisco routers, has 5000+ employees, is looking to buy supply chain software within the next year and just read a recent industry white paper, Top Five Strategies for Better IT Security. Collectively, these data elements provide compelling insight of a prospect ready to buy.

Knowing such details, a company is truly a step ahead of its competition in interacting with such a prospect. Once these prospects are identified and intelligence collected, the next step is to engage these prospects by using relevant content.

Using content to accelerate engagement

At this point in the sales cycle, most companies turn to internal and external content that can include brochures, sales sheets and even industry specific information from outside sources. While this is a good start, this information is sometimes distributed without regard for specific ‘pain points’, educational needs or current interests of individual prospects within an account.

However, predictive analytics allows content marketers to learn – and act on – what is trending with specific accounts. This allows more targeted and relevant content selection, including third-party content assets. This is particularly important in the tech market where there may be many individuals within one enterprise who are decision makers, users and influencers – each of whom may have distinct content needs.

A content library enables a company to share selected, relevant information with each prospect. To be even more useful to the prospect, content should be available in a variety of media, such as print, e-books, checklists, assessment tools, social content, video or case studies, to meet the needs of individual influencers. Now, instead of a sales person being the vendor of a product or service, he or she is a credible and accessible strategic resource, providing targeted information and engaging prospects with discussions about subjects they care about.

For instance, if a solution provider has targeted sales and marketing software companies as accounts, then research reports focused on marketing and sales alignment or how to effectively streamline sales workflows likely will be more relevant to individual buyers and influencers in this account – supportive of the lead nurture and sales effort.

A variety of media – from ‘snackable’ social posts to detailed case studies to video – will help sustain interest as well. The CFO in the account might well appreciate cost savings or revenue opportunities information pertinent to the subject, while CMOs might appreciate details on building a better dashboard for targeting and attribution.

Engagement science combines account-based intelligence, predictive analytics and relevant research-based content, readily accessible and on-demand. Companies that embrace this approach will move from a one-size-fits-all sales cycle to an individualised approach that increases the speed of the lead nurturing and sales cycle and helps to develop sustainable relationships with customers.

Have an opinion on this article? Please join in the discussion: the GMA is a community of data driven marketers and YOUR opinion counts.

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