Every business needs an effective and productive sales team to sustain its presence in the market. However, in today’s technology-driven times, it is not just about the quality of the personnel in the team, it is also about how best to maximize the endless amount of information or data gathered throughout the entire sales process.
According to Zion Market Research, the global data/predictive analytics market is expected to reach approximately USD 11 billion by 2022. Meanwhile, the International Data Corporation forecasts that revenues for big data and analytics in the Asia Pacific region will reach nearly USD 15 billion this year, an increase of 14.4 percent in 2017.
In an age where data holds the key to business sustainability, it is easy to see why these numbers continue to climb as more organizations start to appreciate the value of having strong data analytics. However, I am increasingly coming across businesses who struggle to understand how to leverage the data they have or to know how to make good use of them to support their sales functions.
There is perhaps no other department within a business that generates more data than the sales department. With almost every activity within the sales function being measurable, the key is to know how and what to keep track of, as well as how best to use these data/measurements.
Sales data analytics can be loosely defined as the practice of monitoring sales metrics, generating insights from data and trends, and ultimately using this data to optimize activities, define targets and forecast future sales performance.
The market today is filled with both generic off-the-shelf software tools and customizable solutions that claim to help you achieve the above objectives. Many of them will help you track the following metrics:
When used correctly, these tools can substantially improve the performance of a sales teams in many areas. The benefits include better lead generation, enhanced field productivity, optimized dynamic pricing, better customer profiling, maximized customer lifetime value and increased cross-selling/upselling.
One of the biggest motivators of data analytics in sales operations is its ability to assist in upselling initiatives. Upselling is a sales technique where the seller tries to persuade an existing customer to upgrade to a related product or service with the purpose of making a larger sale.
Having a tool that can automatically prompt the salesperson of the customer’s purchase history, general interests and specific preferences comes in handy to help upsell a transaction. When sourcing for a suitable upselling tool, zoom in on its ability to provide useful features such as product clustering, market-basket analysis and predictive modelling.
What these features mean is the ability to provide your sales force with an omni-channel view of the customer throughout the consumer journey over time and across multiple touchpoints such as social media channels, e-commerce sites and in-store facilities.
One of the more effective tools to support upselling is the use of recommendation engines. These are powerful algorithms that help businesses to determine the best products and promotions for their customers.
Research shows that this tool is instrumental in reducing customer churn, increasing customer satisfaction and driving revenue for sales-orientated businesses. Using an example from a client of ours in South East Asia, the company fed the recommendation engine with three years’ worth of data including customer purchasing history, product details and promotions to help support its telemarketing and online business-to-business sales activities.
The system proceeds to automatically recommend and highlight the specific promotions and products to their customers so that they do not need to search through all the available promotions, which could amount to more than a thousand active promotions at any one time.
As the consumer journey or buying behavior grows increasingly complex, your sales force has no choice but to adapt quickly to this continuous shift. Being able to optimize your sales team’s effectiveness and productivity could very well be the key for your business to stay in the competition.
Michael Hutab is DKSH’s Chief Information Officer since May 2016. Based in Kuala Lumpur, Malaysia, he is responsible for the Group-wide IT strategy and its implementation and for driving forward continuous improvement of business processes through innovative IT solutions.