Companies can reap huge benefits by optimising their marketing and advertising spend through advanced analytics.
With double-digit inflation impacting almost every sector of the Indian economy, rising interest rates and uncertainty in the overall economic scenario, almost all companies are aiming to control costs.
Advertising is indeed a big line item in the profit statement of companies. For financial year 2008, advertising and marketing expenses amounted to Rs 7,065 crore (for the top 200 Indian listed companies in terms of their net sales). These expenses are 12 per cent of their total selling and administrative expenses, which is no doubt a sizeable piece. For some sectors such as fast-moving consumer goods, media and financial institutions, this figure is as high as 60 per cent.
However, while implementing cost-cutting measures, most CEOs, CFOs and marketing heads seem to be rather hesitant to touch advertising, which is regarded as the holy cow. At the same time, they resonate with the observation by John Wanamaker, “Half the money I spend on advertising is wasted; the trouble is, I don’t know which half.”
It is a difficult task to segregate the two halves because they are intermingled. The reasons behind this are, first, there are not many measurement systems to determine and account for what is yielding results and what is not.
Second, there is a complex mesh of multiple advertising channels such as the television, print, radio, cinema, outdoor and internet — each highly cluttered.
Having said this, with shrinking bottom lines and CEOs demanding return on investment (RoI), the critical questions the business faces are: “Why am I spending this money?”, “Can I do it with less?”, “What benefits does it actually provide to my business?”, and “Which of the channels is the most effective?”
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These questions can be answered by effective measurement, optimisation and monitoring. Measurement helps in identifying and demarcating the high impact campaigns. Optimisation enables investment in the best-performing initiatives. Monitoring is important for tracking effectiveness and identifying scope for further improvement.
The following examples exhibit how companies across the globe have benefited by using advanced analytics to solve their business problems related to marketing spend.
ANALYTICS QUANTIFIES BENEFITS FROM EACH MARKETING PROGRAMME: One of the world’s leading consumer durables chains was struggling to allocate its marketing resources effectively across its various geographies and product combinations. The company had 14 product categories in more than 200 countries in a total of 476 category-country combinations.
The company statistically tested each of these 476 combinations in terms of the impact of different marketing initiatives o n their product sales. Models were built to map the relationship between the marketing expenses, channel and corresponding RoI.
These models revealed mismatches between some of the company’s marketing investments and the corresponding benefits. Millions of dollars were saved and the company was able to rightly allocate its marketing expenditure.
ALLOCATION OF AD SPEND TO IMPROVE EFFECTIVENESS: A leading manufacturer of computer peripherals, which underwent a controversial merger, was spending $300 million a year on advertising to communicate its new identity. The top management wanted to understand the RoI of advertising in both brand-building and customer-purchase decisions. Moreover, the management also wanted to optimise spend allocation between its two existing programmes — corporate-wide advertising and segment-specific brand advertising.
Econometric models were built to understand the impact of ad expenditures on both brand perception and sales. The model results made it apparent that the segment-specific brand advertising was more effective than the corporate-wide strategy as its revenue impact was five times that of the latter.
The company benefited by scaling down its corporate campaign in favour of the segment-specific ads. Also, amongst the multiple segment-specific campaigns, the most effective promotion was identified where the benefits were three times the expenditure. Streamlining its business process, the company is estimated to save as much as $5 million a month.
OPTIMISATION HELPS IN REDUCING LOYALTY PROGRAMME COST AND MAXIMISING CUSTOMER LIFETIME VALUE: A leading European airline, as part of its loyalty programme, was conducting numerous marketing campaigns with multiple objectives, targeting more than 500,000 customers. The airline felt the need to reduce the cost of its loyalty programme while maximising the lifetime value of its members.
| AD-SPEND OPTIMISAION TECHNIQUES |
| Multivariate analysis: Separates the signal from the noise in data with many variables and extracts essential information such as key drivers of sales. |
| Distributed lag modeling: Explains the variation in sales on the basis of current and lagged values of the drivers of sales. |
| Marketing-mix modeling: Measures the impact of marketing activities, competitive effects and market environment on sales of a product. |
| Design of experiments: Uses methods to quantify relationships between different factors affecting a process or outcome of a process. |
Loyalty and customer value scores for the members were developed and they were segmented on the basis of their scores. Evaluation of the marketing efforts was done on the identified segments on the basis of both their cost and revenue impact on the customer lifetime value. Thereafter, simulation techniques were applied to find the optimal marketing spend distribution that maximise the value generated by a customer over a given time horizon and at the same time reduce cost of the overall loyalty programme.
Through optimal diversification of marketing actions and targeted customer profiles, the airline was able to optimise its business performance by improving marketing efficiency and effectiveness across the customer portfolio.
THE RIGHT MEDIA, AT THE RIGHT TIME, IN THE RIGHT AMOUNT: A leading North American advertising agency faced the problem that most of its clients’ advertising money was wasted because it was in the wrong media, at the wrong time, in the wrong amounts.
To solve this problem, sophisticated forecasting models were built on daily data for individual stores/outlets across geographic units. These models helped the agency in identifying the critical factors driving sales.
With the help of these models the agency could spell out in great detail which marketing and advertising channels were most effective and how much to spend on them and when.
Significant savings were realised by the models which not only identified the non-profitable channels of advertising, but also enabled reallocation of that spending to meet future revenue targets.
JUDICIOUS SPEND OF ADVERTISING MONEY: One of the largest banks in the US wanted to use its advertising dollars in the most effective way possible and understand its impact on customer acquisition efforts. Econometric models were built to determine the influence of various modes of advertising messages on customer’s decisions to accept services provided by the bank. Also, better channels of advertising were identified having minimum cost of customer acquisition.
The bank was quickly able to realise that it could reduce spending in some traditional media by as much as 50 per cent. The models exposed the medium where the bank overspent and this helped the bank in reallocating ad-spend more profitably in order to meet business goals.
Thus, it is evident that companies across the globe, who use advanced analytics to tune their marketing and advertising spend, do reap a higher RoI on ad spend, to the extent of 20-30 per cent.
Quoting A G Lafley, Procter & Gamble chairman-CEO, “…P&G is getting real traction from marketing RoI and market-mix modeling work.”
But what does this mean for Indian companies? Is solving the ad-spend RoI riddle possible? Can it be measured and quantified? Can this huge quantum of marketing spend be optimally channelised?
The answer is yes. Today, Indian companies are data-rich. Their IT platforms hold abundant data on sales and marketing by geographies and product categories. The marketing and advertising managers have information on ad-spend by various advertising vehicles. All they require to do is to harness advanced analytics for syndication, mapping of patterns, quantification of relationships and optimisation. Once this is done, companies can get a big bang for their buck.
Harsha Kapoor is practice head, analytics solutions, Tata Strategic Management Group, and Rituparna Dasgupta is an associate consultant at the same organisation