In my last post, I discussed the current state of Sales 2.0 sales intelligence products and promised to address the future of these services. So let’s dive right into the subject…
I see in the next few years an evolution of these products towards higher productivity and ROI for sales departments as vendors continue to refine the accuracy, timeliness, completeness, and pervasiveness of sales intelligence services. These tools will continue to expand the breadth of aggregated content and leverage emerging predictive analytics software to provide better tools for determining Who to Call, When to Call, and What to Say™.
You will see sales triggers continue to improve and evolve. While today, most vendors provide between twelve and eighteen trigger types (iSell offers three dozen), the number of triggers will grow with the development of verticalized triggers targeting specific industries. Furthermore, you will see a greater refinement in both the granularity and precision of sales triggers allowing for a stronger signal to noise ratio.
A broader set of analytics will be incorporated into these tools. These will include tools for
· Sales Directors: Dashboards and forecasting, territory planning
· Sales Operations: Improved usage reports, ROI calculators, launch and training tracking
· Marketers: Segmentation reports, lead scoring, lead routing, conversion ratios, buying trigger identification
· Sales reps: Account planning recommendations, opportunity scores, product recommendations, refined alerting
One exciting area is the ability of predictive analytics tools to identify the key triggers and attributes of your top customers. While historically, targeting was limited to segmentation based upon firmographics and job functions; predictive analytics identifies buying signals across a vast array of news, company websites, job boards, filings (e.g. patents, trademarks, UCC), social media, and other structured and unstructured information sets. Not only does predictive analytics survey a broader scope of content for buying signals, but they detect signals that may not be evident to your sales and marketing teams. These signals can then be used to refine your definition of best customers and prospects and evaluate leads against these indicators. From this broader set of sources and trigger types, you may identify new clients in non-traditional verticals and focus sales and marketing efforts on your top priority leads as scored by the predictive models. Furthermore, the predictive models will recommend products and sales messaging in line with the mined intelligence.
Sales intelligence services are already well established in CRMs. Not only do they provide integrated list building and real-time display of account, contact, and lead profiles; but they also support data quality within CRMs via on demand “stare and compare” updates and scheduled batch refreshes. These tools help ensure that verified data is loaded and maintained with your CRM. When predictive models are applied, your leads will be rescored on a regular basis and new opportunities dynamically scored as part of the initial enrichment of new records.
As the sales intelligence services continue to extend their value proposition, they will move up the marketing funnel and begin to enrich marketing automation platforms with firmographic data and predictive analytics. There will be multiple benefits to platforms such as Marketo and Eloqua. Accurate enriched data provides improved lead scoring, routing, and nurturing; campaign targeting; and segmentation. Predictive analytics company Lattice Engines has even suggested that fewer marketing qualified leads will be passed to sales reps, but that the quality of the leads will be so much higher that the percentage of closed leads combined with larger deal sizes will result in significant revenue growth.
Sales intelligence tools will become pervasive across platforms and location. Today, you find them in web browsers, CRMs, and tablet browsers (via Safari). With the new HTML5 browser standard, sales intelligence services will be able to leverage mobile app features such as alerting and location awareness within browsers. Furthermore, the services will be more context aware. For example, if a sales rep is meeting with a client later that day, a mobile notification may be displayed about a breaking event (e.g. sales trigger, service issue) instead of waiting for the daily email alert. Likewise, if the rep is traveling to meet with prospects in another city, the platform might suggest other potential prospects or clients with whom to meet or suggest potential case studies to review prior to the meeting.
In short, context and availability will continue to improve with sales reps moving away from sales intelligence services as destination sites (e.g. OneSource iSell) and using them more as ubiquitous information services delivering on demand, contextualized intelligence across many platforms. These powerful tools will extend into the marketing function, providing enhanced lead management as soon as leads are entered into cloud or on premise platforms. By providing immediate lead enrichment and predictive scoring, both sales and marketing will become better aligned and more effective.