Data-driven sales using strategic revenue, margin and white space Analysis in SAP Marketing Cloud

The internet has structurally changed sales field operations. In the past, salespeople played a vital role in influencing purchasing decisions although with the prolific amount of information now available consumers are significantly further down the sales funnel in that they are more educated and have access to more information about products than ever before. This new intelligence paradigm has sparked a real shift in the type of selling techniques required to be relevant in today’s environment.

Salespeople are now required to be trusted advisers, coaches and consultants that genuinely assist and guide the customer to make more accurate and knowledgeable business decisions based upon data-driven insights. This shift in the sales approach is proving to be critical – businesses are focussed on data and analysis to ensure the long-term viability of their enterprises where there is a real focus on driving revenue and maintaining competitiveness.

Marketing technology advancements in recent years are enabling sales teams to be more informed and effective thereby fostering a greater synergy between the marketing and sales departments. This shift has placed more pressure on marketing departments to demonstrate their value and contribution to enterprise revenue and profit. Successful marketers have shown us that to achieve this contribution through the successful use and adoption of Marketing Automation. These types of technology platforms aggregate customer data such as sales history and behaviour, and interactions which can then be leveraged via highly targeting automated campaigns and presented as visualisations to the sales field via the CRM to express key learnings.

To be effective sellers, salespeople require real-time data that compares and contrasts customer spend, revenue, margin discounts and customer satisfaction. This invaluable information will guide the conversations salespeople have with their customers allowing for astute and strategic recommendations that deliver measurable value to the customer.

SAP Marketing Cloud is an optimal tool that is designed to provide these types of data-driven insights including:

  • Guided analysis and product recommendations

  • Identification of customer purchasing potential

  • Exploration of customer lifetime value and pocket margin

  • Increased margin and discount visibility

SAP Marketing Cloud provides four tools that assist salespeople via data-driven insights including Relationship Analysis, Whitespace Analysis, Margin Decomposition and Customer Stratification. In this article, we will explore how White Space analysis provides key insights into untapped opportunities.

Whitespace analysis

Whitespace analysis provides a powerful opportunity that helps identify cross-selling and up-selling opportunities within existing accounts. SAP Marketing Cloud ingests ERP Financial and Sales data where predictive modelling is applied conducting in-depth analysis of customer accounts. This enables sales people to leverage gaps identified.

SAP Marketing cloud performs the following calculations:

  • Customers average revenue distribution contrasted against current purchases

  • Revenue distribution contrasted against other peers’ (like/similarly profiled consumer/customer) purchases including margin per product segment

  • Examines the customers highest value product group, sets this at the target value then scales other product groups according to this value and calculates expected revenue potential across other product groups

  • Finally, SAP Marketing Cloud then calculates the difference between actual and target values and presents this as whitespace that represents purchasing potential of the customer and an opportunity for sales to ‘fill the gap’

Example

The customers of customer segment X bought in product segments A, B, and C with the following distribution: A: 10%, B: 60%, C: 30%.

The current customer also buys in these three product segments but with a different distribution: A: 2,000 AU (20%), B: 3,000 AU (30%), C: 5,000 AU (50%).

5,000 AU is the highest purchase value and is taken as achieved target value of 30% of the target distribution. For the current customer, this results in the following target values per product segment: A: (10% / 30%) * 5,000 AU = 1,667 AU, B: (60% / 30%) * 5,000 AU = 10,000 AU.

In product segment A the current customer has bought approximately as much as the peer group. For product segment B the system identified a gap of 10,000 AU – 3,000 AU = 7,000 AU. The customer has a purchasing potential in this product segment and presumably buys the corresponding products elsewhere.

As demonstrated tools such as Whitespace Analysis arm salespeople with real-time insights that allow them to be more effective in the field. Companies that do not innovate and adopt these emerging technologies run the risk of obsolescence and invite competitor encroachment.

Get in touch
Explore how Bluleader can assist you with the successful implementation of your CX strategy.
Get in touch
By |2018-09-08T03:27:42+00:00September 7th, 2018|Data Driven sales, Marketing Automation, SAP|