The success of sales executives, Irrespective of the industry they operate in, is heavily reliant on how well-informed they are and how they are able to use this information to take accurate, data-driven decisions in the shortest time possible.
Gartner predicts that, by 2022, more than half of major new business systems will incorporate continuous intelligence that uses real-time context data to improve decisions.
This is especially true for FMCG sales teams where money is directly proportional to two factors – speed and accuracy.
Over the last few years, I’ve worked closely with several Fortune 100 FMCG companies like Reckitt Benckiser, Britvic, Unilever etc. During this time, we’ve seen an increase in primary sales by 5% and secondary sales by 15%.
In this blog, I’ll be drawing on these experiences and address how an intelligent BI system can be a powerful asset for FMCG sales teams and enables them to take complicated decisions at a fast pace.
Before discussing how a data-science and AI powered BI system can help, let’s start by taking a look at the common challenges faced by FMCG sales teams today.
Unlike other industries, sales in the FMCG industry depends on a wide range of influencing factors. As the consumer base is enormous and spread across different locations, influencing factors vary from one country/state/county to another.
Some of these factors include:
The sales teams should not only plan for the current environment, but also should be able to accurately forecast for the future, based on all these factors.
Since the industry is a consumer-facing one, external factors like weather, events, emerging local players etc. will also affect primary and secondary sales.
Taking into consideration all these factors, we can say the success of any FMCG sales executive depends on.
How fast he/she can take the most data-backed decisions which have the highest probability to yield the maximum buck per dollar spend.
In order for this to happen, the sales representative must be equipped with an intelligent Business Intelligence system which can detect, recommend and forecast the most accurate market trends.
However, most FMCG sales teams still rely on a traditional BI system which takes the historical/routine data from internal LOB systems, market research or syndicated data providers like Nielsen, IRI, SPINS etc.
In an industry in which sales is affected by a plethora of direct/indirect influencing factors, the use of such routine data results in a lot of missed opportunities.
In addition to this, in most cases the BI system won’t be a self-service one. Meaning, sales teams have to hover around the IT department/MIS teams/developers for getting new reports.
Since these reports can’t be updated, sales teams again have to check other unstructured data in the form of spreadsheets to take decisions.
This lack of real-time analytics, presentation of data in unstructured formats, the need to check multiple reports in a traditional BI also leads to poor usage of existing data and increase of intuition-based decisions and forecasting among sales teams.
Needless to say, most of these traditional BI systems suffer from low adoption rates too.
Now that we have discussed the general challenges of FMCG sales, let’s discuss the must-have characteristics of an BI system to overcome these challenges.
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An intelligent BI system should be equipped with data from a range of consumer touch-points. The data should be a combination of:
Internal data: Data about primary sales, secondary sales, POS, market research, promotions, past campaigns etc.
External data: Data about weather, social, events, location, search analytics, TRP, events etc.
Since the data includes such a huge combination from various resources, sales execs can take THE most data-backed decisions in different key scenarios. Some of these could include:
As mentioned earlier, an FMCG sales executive should not only strategize for the present but also plan for the future.
And the future of FMCG sales again depends on various factors such as consumer behaviours, seasonal changes, occurrence of important local events, competitor strategies etc. – You get the idea.
An intelligent BI system should not just detect and recommend promotion, pricing and other sales strategies for the current scenarios, but also be able to forecast for the future.
The system should be powered with Predictive Analytics which can prescribe effective insights for the future based on the existing patterns and trends in the internal and external data (as referred above)
With predictive analytics, sales execs can accurately forecast…
Sales teams have to go through a series of reports to understand different trends, scenarios, fluctuations etc. This information takes time to analyze and won’t be very intuitive to make decisions.
An intelligent BI system shouldn’t be limited to just reports. It should possess advanced visualization components and data models for a clearer and comprehensible demonstration of information.
With such advanced data visualizations, executives don’t have to switch various reports for obtaining relevant information. These customizable dashboards allows users to obtain relevant information in a single window view.
The use of these solutions will also enable sales to have a single window view with marketing and thereby resulting in a tighter marketing and sales alignment.
The BI system should have both push and pull mediums. It’s not humanly possible and also time consuming for a sales exec to manually check each trend and report in the system.
In such cases an Artificial Intelligence powered Chatbot might just serve as the perfect solution.
With an AI chatbot, sales teams can simply ask natural language question like “what is the net revenue in Washington” and the bot can take data from the system and present it before executives within seconds.
Sales teams can access crucial data at their fingertips. They don’t have to scour over umpteen reports before making a decision.
If the bot is integrated with the the organization’s popular messaging platform like Skype For Business, Slack, etc., users don’t even have to open the BI software for obtaining information.
The push and pull mediums of a chatbot allow it notify any immediate or upcoming sales anomalies/opportunities to the concerned executive.
In addition to these, the chatbot can present information in multiple formats – rich media, text etc. (You don’t have to look at an entire report to find some sales figure)
Users can access data from the bot even from their mobile phones.
All these unique features of a bot skyrocket the adoption rate of BI system too. An AI powered bot simplifies the complex process of using a BI system.
While the adoption of advanced BI system looks like a massive change management process, in real-time your sales teams will just be using a AI bot which can fetch only the most spot-on information from an ocean of qualitative data in the BI system.
Sales reps don’t have to go through any additional training or learn new skills for using the system.
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Hemanth handles Acuvate’s Analytics & Database services. He was previously heading the Innovation lab & Tech readiness department at Acuvate. His current role demands to provide Delivery Oversight, ensuring the team’s readiness and managing the service portfolio of Analytics and Database Practice. Hemanth has consulted various Manufacturing, FMCG and BFSI clients on large scale Data related initiatives. Hemanth has been a part of Acuvate for more than 5 years now.
Hemanth Kumar