Sales Analytics; HBR Research – New Age of B-to-B selling

Harvard Business Review published an excellent research report in March 2014 how sales analytics can be applied to optimize salespersons’ time and enable account managers to identify and pursue with the right prospects.

Over 60% of research respondents seek to improve opportunity and lead management by better sales intelligence. By having the right data sales representatives can rank customers based on win probability and expected revenue.

Due to internet and social media, customers are already knowledgeable about products that they buy when a salesperson visits them. Therefore salespeople seek to have more educated and consultative discussion about product recommendations and proposing the best product & solution combination.

 

 

Benefits from sales analytics:

Saved time

• Some salespeople saved even 40% of their time by minimizing ineffective sales calls

Digital footprint extends understanding of the customer

• Marketing departments analyse web page traffic and customer behavior such as downloads, frequency of visits, products viewed. This data can be combined with social media data.
• Combining to web behavior to e.g. resent service calls and ordering activities will give a 360-degree view to customer data.
• Now it will be easier to propose right products to customers, understand customer interest and understand similarities between customer types.

Predictive analytics and accurate forecasting

• Lead scoring and predictive outcomes help sales representatives to use their time effectively. This will help sales organizations to focus on opportunities that will most likely to close. Predictive analytics provide understanding of the length of the sales cycles and opportunity margins per customers.

Infolets – meaningful data to mobiles

• Mobile usage will dramatically drive salespeople adaption to use analytic tools and capabilities. In order to enable effective mobile usage data needs to be in visual dashboards, infographics and should have easy drill-down capabilities.
• As salesperson is always on the go, information should be in real time. This will not only save sales representatives time, but enable to have up to date discussions with the customers.

I believe predictive sales analytics will provide a whole new world of data that has hardly been explored in the manufacturing industry. Companies have put their analytic focus on optimizing production capacities, but this is no longer enough. Those companies that will systematically develop predictive sales analytics will show healthier growth compared to companies that keep relying only on individual salespersons knowledge.

Which function should operate sales analytics?

HBR research paper didn’t analyse which organisation should own and execute the data analysis. Sales departments surely need to have the data available, but in which organization the best competences are located? Marketing departments normally have good knowledge of customers’ needs and digital footprint; however they many times lack knowledge of sales needs.

I believe sales department should have ownership of the analytics service.  Therefore, combining the knowledge of marketing and sales is crucial. I think the best combination would be that marketing department will operate the service for sales and work closely with financial and customer service teams. This would enable long term systematic approach to combine various sources of data.

Naturally, this will require marketing organisation to extend traditional web traffic analysis and customer intelligence capabilities. Responsible sales analytics person needs to visualize and combine data from ERP, CRM, customer service team and web traffic and serve the data into easily digestible mobile optimized formats. This requires new set of capabilities in marketing organisations. This will requires adaption of big data thinking to a whole new level not only in marketing department but also in sales organisations.

Download Research report directly from HBR Analytics services: The New Age of B-to-B Selling