L33: Media Evaluation & Follow-up

Good morning, everyone. Welcome to Lecture 33 of MGA-304. Last class we covered the exciting world of emerging media trends — programmatic, native advertising, OTT, influencer marketing, and AI-driven advertising. Today we turn to a critically important but often neglected practice: Media Evaluation and Follow-up. Once the campaign runs, how do you know if the media plan delivered what it was supposed to deliver? And how do you use that knowledge to improve? [0–10 min: Introduction] Here is a sobering reality. Across the Indian advertising industry, the most common approach to media evaluation is: the campaign runs, sales go up (or they do not), everyone nods or shakes their heads, and the agency prepares for the next campaign. Systematic, rigorous post-campaign media evaluation — comparing actual delivery against planned delivery, understanding why performance differed, and feeding learnings into the next plan — is practiced far less than it should be. Why does this matter? Because without proper evaluation, you are navigating without instruments. You are spending crores of rupees without knowing which crore did the most work. Post-campaign evaluation is not just about accountability — it is about learning and continuous improvement. The brands that improve their media efficiency most dramatically over time are those that invest in rigorous post-campaign analysis. [10–40 min: Core Content] Media evaluation operates at two levels: delivery evaluation — did the media plan deliver the planned reach, frequency, and GRPs? And effectiveness evaluation — did the media activity produce the desired communication effect? Let us begin with Delivery Evaluation. When a media plan is executed, the actual delivery rarely matches the planned delivery exactly. Television ratings fluctuate — a programme that was expected to achieve 3 TRP delivered only 2. A digital campaign was planned to deliver 10 crore impressions but only delivered 8 crore due to inventory constraints. A newspaper failed to run an insertion on the planned date. Media buyers track delivery through post-campaign reconciliation. For television, BARC provides daily and weekly audience data that can be matched against the planned TRPs. For digital, ad serving platforms provide impression, click, and view data in real time. For print, tear sheets — copies of the actual insertions — confirm what ran. For outdoor, field verification confirms that hoardings were indeed displayed. When planned delivery is not met — what is called a shortfall — the media owner is obligated to provide makegoods — additional placements at no charge to compensate for the under-delivery. Negotiating and tracking makegoods is a significant part of a media buyer's ongoing work. If Star Plus delivered 80% of contracted TRPs, they owe the advertiser 20% additional spots. This is a commercial relationship that requires active management. Now let us look at Effectiveness Evaluation. This goes beyond whether the media ran as planned to ask: did the media activity change consumer attitudes and behaviour as intended? The primary tool for this is Post-Campaign Research, which mirrors the pre-campaign benchmark established before the campaign ran. Key measures include: Brand Awareness Tracking. The percentage of target consumers who can name the brand without prompting — unaided awareness — or with prompting — aided awareness. If the pre-campaign awareness was 30% and the post-campaign awareness is 48%, the campaign contributed an 18 percentage point gain in awareness. This figure is then compared against the planned awareness objective from the DAGMAR framework. Advertising Awareness and Recall. The percentage of target consumers who recall seeing or hearing advertising for the brand in the past month. High advertising awareness confirms the creative was noticed and remembered. Low advertising awareness despite confirmed media delivery suggests creative memorability was inadequate — the media plan did its job but the creative did not. Message Association. The percentage of consumers who can correctly associate the campaign's key message with the brand. If Surf Excel ran a campaign with the message 'Daag acche hain' and only 40% of consumers who recall seeing advertising can correctly identify that message with Surf Excel, message communication was incomplete. Brand Attribute Ratings. Changes in consumer perceptions of brand attributes — 'modern,' 'trustworthy,' 'innovative,' 'value for money.' If Asian Paints ran a campaign to improve their 'premium quality' attribute rating and this increased from 35% to 50% among target consumers, the campaign achieved its attitude objective. Brand Consideration and Purchase Intent. The percentage of consumers who say they would consider buying or are likely to buy the brand. This is the most commercially proximate communication measure. In digital media, effectiveness can be partially evaluated using platform analytics — click-through rates, conversion rates, cost per acquisition, view-through rates. These performance metrics provide granular, real-time signals about what is working and what is not, enabling in-flight optimisation. Marketing Mix Modelling is the most sophisticated tool for media effectiveness evaluation. MMM uses econometric analysis to decompose sales into components attributable to each marketing input — television advertising, digital advertising, pricing, distribution, seasonality, competitive activity. It quantifies the contribution of each media channel to sales. HUL, P&G India, ITC, and other large FMCG companies invest substantially in MMM. It answers questions like: 'Of the Rs. 50 crore we spent on television advertising, how much incremental revenue did it generate?' and 'What would our sales have been if we had shifted Rs. 10 crore from television to digital?' Attribution Modelling in digital marketing addresses a related problem: when a consumer makes an online purchase after being exposed to multiple advertising touchpoints — a YouTube ad, then an Instagram ad, then a Google search ad — which touchpoint gets credit for the sale? Last-click attribution gives all credit to the final touchpoint before purchase. First-click gives all credit to the first touchpoint. Data-driven attribution distributes credit across all touchpoints based on their statistical contribution. Each model gives different strategic implications, and choosing the right model is critical for correctly evaluating each media channel's contribution. Media Audit is another evaluation tool, particularly useful for large advertisers managing multiple media agencies or complex multi-channel campaigns. A media audit is conducted by an independent third party who examines all media purchases — comparing rates paid against market rates, checking delivery against contracted amounts, verifying trading terms. In India, media audit firms like Ebiquity and Accenture Song conduct these audits for major advertisers. Audits frequently uncover that brands are not getting what they paid for — a finding that has significant cost-saving implications. [40–55 min: Activity and Discussion] Activity. You are the media manager for a Goa Tourism Board campaign. The campaign ran for eight weeks across television, digital, and outdoor with a budget of Rs. 5 crore. The planned objectives were: reach 50% of domestic leisure travel intenders in Maharashtra and Karnataka, generate 2 lakh clicks to the Goa Tourism website from digital ads, and increase intention to visit Goa in the next six months from 35% to 50% among reached consumers. Post-campaign, you receive this data: Television delivered 380 TRPs against a planned 420 TRPs. Digital ads generated 1.85 lakh clicks against a planned 2 lakh. A post-campaign survey shows that among consumers exposed to the campaign, 44% intend to visit Goa in the next six months (up from 35%). Evaluate the campaign against each objective. What worked? What did not? What would you do differently next time? Take three minutes. Discussion: Television underdelivered by about 10% — you should claim makegoods from the channel. Digital underperformed slightly on clicks — investigate whether creative or targeting was the issue. The attitude objective — intention to visit — increased by 9 percentage points, which is a strong result, though it fell short of the 15-point target of 50%. Overall a moderately successful campaign. Recommendations for next time: stronger creative testing before the campaign to ensure higher digital click-through, and negotiate stronger television positions during higher-rating programming. Discussion question: If post-campaign research shows that your brand's awareness increased significantly but sales did not move, what conclusions would you draw? Is this a failure of the campaign? Not necessarily a failure — awareness is a necessary but not sufficient condition for sales. Other factors may be preventing conversion: inadequate distribution, pricing, or competitive offers. The advertising did its communication job. The commercial conversion failure may lie elsewhere in the marketing mix. [55–60 min: Summary and Assignment] Today we covered media evaluation at two levels: delivery evaluation — GRP reconciliation, makegoods, digital impression verification — and effectiveness evaluation — brand tracking research, advertising recall, message association, MMM, and attribution modelling. We discussed media audits as an accountability tool. We applied all these concepts to a Goa Tourism case exercise. Assignment: In 200 words, explain why brands that invest in rigorous post-campaign media evaluation consistently outperform those that do not. Draw on at least two concepts from today's lecture to support your argument. Next class — Lecture 34 — we move into the evaluation of advertising effectiveness more broadly — testing approaches, research methodologies, and what we can and cannot prove about advertising's impact. See you then.