Organizations today are increasingly focused on executing targeted marketing campaigns and majority of them are doing so by leveraging data and by spending excessively on customer analytics. However, a critical area that organizations should emphasize is reconciling of the marketing spend. Not being high on the risk radar, often this goes unnoticed in the bigger scheme of things. However, a little due diligence can save big bucks and in the long term serve as a big deterrent to the party at fault.
Marketing function devotes a large part of its efforts on managing and negotiating deals with agencies - get good slots for a cheaper price, bulk discounts and promotional schemes, etc. However, once the plan is in place, verifying whether the returns are in line with the expectations is lacking with most of them conducting manual/ ad-hoc checks on sampled data. Some of the aspects that could help organizations verify are:
- Comprehensive reconciliation of exact media placement vs. the media invoices
- Duration of ad aired vs. invoiced
- Delivery of ‘make-good’ spots if the program does not generate viewership (TRP) that was forecasted
- Various forms of pricing discrepancies
- Actual delivery of promotional/ bonus exposure offered
ZenithOptimedia estimates that the global ad expenditure will reach USD 545 billion by end of 2015 with Television taking up the biggest chunk. But are these expenditures giving organizations the desired or expected outcomes? Do they actually reach the right audience’ through the right channels?
Audience measurement systems can serve as a reliable source of measuring actual media placement and their returns. And comparing that with media invoices from your external media partners throws up some glaring discrepancies. The challenge in correlating the two lies in the plurality of items on both sides along with differing data formats - which is addressed by application of rule based analytics using big data. Verifying the delivery of compensatory and promotional spots, however, calls for machine learning techniques to identify suspicious patterns.
In Wipro's Apollo implementation at a consumer products company - which had outsourced television air-time distribution planning for its 6 products across 124 national and local channels (in categories such as entertainment, movies, news, music and informational) - the starting point was to identify whether the agency had billed the company for a prime time slot. Prime time is when most people sit down to watch television after dinner, at the end of the work day. However, certain popular shows could get eyeballs from stay-at-home parents/ retired people/ kids during the afternoon making them prime too.