How do you compete in a fiercely competitive market like CPG? Getting the product to market is only half the battle won. Getting the buyer to pick your product is the other half. Trade Promotions help you achieve that but how do you make them effective? Data analytics to the rescue!
In this blog Jainendra Modi writes about the business needs for Trade Promotion Analytics (TPA).
While there are tons of resources available on the web that talk about the importance of Promotion Analytics solution for CPG companies, there is hardly anything that mentions about expectations on the implementation journey.
Nielsen, a leading global information & measurement company, found that consumer product companies spend about $1 trillion each year on trade promotions and much of that is poorly spent. So much so that approximately two-thirds of promotions don’t even break even.
Trade promotions invariably impact the success of your product and correlate to your top-line. So, let me take you through the business need for a Promotion Analytics solution implementation. And by the way, these are my personal learnings while implementing these solutions for some of our prestigious customers who are industry doyens. So if you are a client or a vendor looking at implementing a Promotion Analytics solution, this is for you.
While the overarching requirement is that the business users should be able to analyze trade spend effectiveness and efficiency for promotions, it makes sense to break this requirement into more manageable pieces that the solution will deliver. These are important as they may not be stated explicitly but a viable solution should pack all the below requirements:
- Automated acquisition and integration of data:
This refers to acquiring and integrating data (e.g. promotions, product hierarchy, customer hierarchy, period hierarchy, shipment and sellout data, reference data) from disparate sources – some in IT systems and others in spreadsheets. All issues and exceptions, both technical and business, are flagged so that required actions can be taken by the business users through a user-friendly interface. Give users the control over all the data so that they can harmonize, enhance, resolve exceptions and override data with necessary audit logging. Derive and store metrics, layer after layer, to come up with the key KPIs that facilitate promotion evaluation.
- Operational reporting for promotion planning:
This pertains to the pre-promotion estimation of effectiveness and efficiency based on planned data. This should also highlight any issues with promotion planning as exceptions that need to be resolved before the promotion is finalized. Pre-defined reports should be supplemented by user-friendly access for ad hoc data analysis.
- Promotion Performance Evaluation:
Post-promotion effectiveness and efficiency calculation of a given product at a specific retailer, for a specific period of time, is utmost crucial. A promotion may include price discounts supplemented by various promotional mechanics (in store, shopper marketing etc.). As with all the reporting projects, this would need pre-defined reports and dashboards.
- Ad Hoc Reporting and Analysis Platform:
The usability can be enhanced by exposing all the sourced and integrated data into a consistent reporting and analytics platform that gives users the flexibility to slice and dice data across multiple dimensions. This platform should also help users get answers to analytics questions on identifying factors influencing promotion performance, predicting sales uplift and overall promotion performance, maximizing trade spend, etc.
- Legacy Data:
Migrate and integrate historical promotion data and perform necessary validation and reconciliation for all the metrics – new system vs old.
The above business needs are the most relevant ones associated with promotion analytics.