Effective marketing accountability requires a mix of art and science
Proof of cause and effect has become a complex issue that requires many parts of the marketing jigsaw to be linked together, says Frank Harrison, strategic resources director at ZenithOptimedia Worldwide.
In the past ten years, most acutely after the dotcom bubble burst and in the current global recession, marketers and their agents have been working harder than ever to identify the best way to measure and plan marketing returns.
We are learning that accountability is as much about the art of corporate culture as it is about the science of cause and effect. But what are the most effective approaches to marketing accountability?
“The time has come when advertising has in some hands reached the status of a science. It is based on fixed principles and is reasonably exact. The causes and effects have been analysed until they are well understood. The correct methods of procedure have been proved and established. We know what is most effective, and we act on basic law.” These words were written in 1923, in the book Scientific Advertising, by Claude Hopkins, a founder of the ad agency that became Foote Cone & Belding.
In 1923, most advertising was in print and involved a direct response mechanism. Remarkably, most of Hopkins’s guidelines are still being practised today. For anyone involved in digital marketing, this 86-year-old book is a worthwhile and salutary read. While technology may change over time, the human response to marketing remains largely the same.
Challenges of the digital age
Today, however, we live in a very different marketing environment. Proof of advertising
cause and effect is a much more vexed issue. In just a few years, the volume of influences on consumer purchase decisions has grown hugely, both those within and outside the control of brand managers. There have been big changes in consumer attention and responsiveness to marketing activities. Consumer decision-making has become more complex, as has the business and marketing environment. It is harder today to understand
cause and effect, and for marketers to build and act on knowledge of what works and what doesn’t.
In its Marketing Accountability Study, published last year, the US Association of
National Advertisers (ANA) stated: “In US companies, both large and small, the goal
of achieving true, demonstrable accountability for the marketing function, if it is considered at all, is one that has proven elusive for years. Yet more and more, senior
management and finance are demanding that marketing provide them with something more than a budget request that is justified by historical performance and ‘soft measures’ with no linkage to financial results.”
However, the ANA reported that only 14% of senior marketers felt confident in forecasts of how marketing activities would affect sales. Paradoxically, in the digital age, marketers are struggling to predict cause and effect.
Creating an accountability culture
The key learning from most surveys among senior marketers is that effective marketing ROI programmes require many parts of a ‘jigsaw’ to be linked harmoniously. Effective ROI jigsaws comprise sections on company structure and processes that are seamlessly linked to those in the areas of data and analytics. The human side of this jigsaw, which
ensures that marketers are ready, willing, and able to measure and effectively plan
return on their marketing investments, has become more crucial.
Survey after survey among marketers show that the greatest barriers to the development of effective marketing ROI programmes are to do with corporate culture, structure and processes. Studies have also found that there are three key components to fostering a successful culture of marketing accountability:
• Chief executive sponsorship. Marketing accountability within any company needs a C-level sponsor – a leader who drives the ROI focus down through the organisation – and the best person to do this is the chief executive. Top-down sponsorship ensures marketing accountability becomes a focus at all levels, not an isolated (and too often unwanted) silo.
• Cross-function collaboration. Marketing accountability depends on close collaboration across stakeholders in areas such as finance, sales, production, research, IT and marketing. Success often hinges on collaborative teams that determine the best measurement of marketing ROI, and together examine and agree the cause and effect of marketing activities.
• Marketing process with accountability at its core. The ANA’s 2005 survey into marketing accountability reported that “the modern marketer is beginningto see marketing as a ‘process’ with measurable inputs and outputs producing reliable, repeatable results. The process approach, which revolutionised the supply side, has finally come to the demand side”. Increasingly, companies are implementing marketing processes that base KPIs and decisions on effective measurement of marketing ROI.
With the right culture of accountability, companies are generally well prepared to adopt best practices in data and analytics. There are essentially three types of measure used to report marketing performance:
● Outputs, such as impressions, GRPs, reach and frequency. These report the size and nature of the audience exposed to marketing activities. They are normally measured via sampled consumer research.
● Intermediates, such as brand awareness, consideration, purchase intent and brand image. These report consumer memories, attitudes and perceptions.
They are normally measured via consumer sample tracking surveys.
● Outcomes, such as sales, test drives, brochure downloads and product enquiries. These report consumer behaviour. They are normally captured at point-of-sale.
The challenge with each of these measures is to tie individual marketing activities to the measured result: to prove cause and effect, either in totality or as a contribution to the effect – and to show how output and intermediate measures contribute to outcome measures in the short and longer term. Successful marketing ROI programmes use these insights on a cyclical basis that plans more effective marketing activities each time around.
Direct response advertisers benefit from apparently straightforward links between marketing inputs, measured outputs and outcomes – and digital media are particularly well placed to provide input-to-outcome metrics. However, the practice of crediting online outcomes to the last ad clicked highlights an issue of cause and effect. Online sales of products are not solely influenced by the most recent click on a banner or search ad. Consumer decisions will be influenced by the product, friends and family recommendations, offline marketing activities and the nature of the website selling the
product – as well as prior exposure to the brand online. The challenge is to isolate the contribution of online marketing activity, and to use the uniquely rapid and low cost testing capability of the internet to create an effective test-refine-improve cycle that delivers improvement in marketing ROI.
Marketing activity that does not include a direct response mechanism, such as that designed to improve intermediate measures, faces a greater challenge when calculating contribution to those measureas and to sales. For example, brand awareness may be influenced by prior use of the brand, seeing the brand in stores, hearing about it from friends or reading about it in print articles or online. Isolating the contribution of marketing from other influencing factors may require either a carefully controlled test, where advertising is the only difference between test and control environments, or mathematical modelling, such as econometrics.
The issue of causality
Proving and predicting the sales effect of marketing requires evidence of cause and effect: proof that the marketing inputs really caused business outcomes, either totally or in part. Yet, despite huge growth in computing and analytical resources, this remains one of the greatest challenges because there are a large number of influences on sales, and many are often more influential than marketing (Figure 1).
For example, during a hot summer, sales of ice cream grow rapidly. At the same time, ice cream advertising increases swiftly. Higher advertising correlates with higher sales. Does this mean that the advertising causes the higher sales of ice cream, or is it the warm weather, or is it a bit of both and, if so, how much of the sales are caused by the advertising? Correlation is not a good basis for saying adspend causes sales gain, unless other possible influences have been accounted for.
One way to examine this might be to look at which brands advertise and which don’t, see if those that advertised achieved higher sales growth than those that did not, and if so, judge that some of the increased sales are down to the advertising.
But this may also be incorrect as there is much else to account for, including brand size. Large brands have more consumers than small brands. They also have greater distribution and larger revenues, and they tend to spend more on advertising. Larger brands – the ones with higher ad budgets – may achieve greater sales gains than small brands. But is this because they have wider distribution, or because they have more customers, or
because of the advertising, or is it down to a mix of these factors? If so, what part does
advertising play? At a simple level, does advertising cause sales response or do higher sales cause greater advertising response? The answer is probably a bit of both. Separating the effects is essential to calculating marketing ROI. This is where econometrics can help.
Econometrics is an immensely valuable tool for calculating the likely contribution of marketing to sales. It works well for advertisers where the necessary time series data exists in the right format for the factors that are likely to have an influence on sales. Marketer surveys have found that most companies with effective marketing ROI programmes include modelling within their set of tools.
But econometrics is not a panacea. It is one piece of the marketing ROI jigsaw. It requires the right type and spectrum of data and budgets to be available for modelling
projects. It can also be weakened when the following is true for a brand:
● When the past is not a fairly good reflection of the future. Econometrics explains the past very well but this may not help in categories experiencing significant change.
● When past brand activity is not a good guide to the best the brand can do. Econometrics cannot assess marketing activities the brand has not carried out in the past.
● Lack of variation in past brand activity can stymie ability to isolate individual effects. If a brand has repeated activity year after year, econometrics can say little about how to improve on that activity.
Ad campaigns, particularly those on TV, are regularly assessed using consumer research that tracks changes in one or more of the following measures: brand recall, ad recall, brand consideration, purchase intent, brand image, brand usage, brand loyalty and (increasingly) brand recommendation. There are normally two issues with using tracking of this kind to measure advertising performance:
● Assumption of causality. There is often an incorrect assumption that the advertising was the cause of change in the tracked measures, when in reality there may be other influencers that have not been measured or accounted for.
● Assumption of ROI. There is often a failure to link intermediary measures to
outcome measures, such as sales. While growing brand awareness may be an
objective for a newly launched brand, the awareness objective is intermediary to the
ultimate objective, which is to grow sales. It is therefore important to demonstrate
that raising awareness via advertising causes sales growth.
Effective use of intermediary measures requires good understanding of the contribution
of advertising to the measures, and the knock-on effect of the measures to other intermediary measures and to business outcomes, both in the short andlonger term. Econometrics is a particularly useful tool to develop better understanding of causal effects between advertising and intermediate measures. It can identify causal effects between intermediate measures, such as between awareness and consideration or between consideration and purchase intent. It can also be used to show causal effects of intermediate measures and sales. Econometrics can help marketers to identify the chain of causality between advertising and sales.
It generally helps to continuously track a number of intermediary measures and to separate them for different consumer groups. For some brands, such as cars, it may be useful to separate measures depending on where consumers are in the purchase decision process.
Comprehensive, continuous tracking data, combined with output and outcome measures, may make it possible to implement ‘live’ econometric modelling, which continuously reports marketing ROI as new data becomes available and guides the forward use of marketing levers.
The marketing ROI jigsaw is different for every firm. Its shape and parts depend on company size, category, culture, structure, process and much else. But for all companies, effective marketing accountability requires a mix of art and science: it requires transformation of culture, of process and of the methods used to measure marketing effects, and to act on the insights from those measures. It requires a top-down focus, collaboration across multiple departments and a marketing process that has accountability at its core.
Marketers cannot rely on output or intermediary measures as proof of marketing ROI. They need detailed knowledge of outcome drivers and of marketing’s contribution to those outcomes.
Where possible, marketing objectives and goals need to be measurable, be measured, and be based on insights from measures. Marketers need to assess and establish causality, and avoid assumptions based solely on simple correlations.
Finally, once embarked on a marketing ROI path, marketers should expect gradual, rather than dramatic improvement in their knowledge and ability to act on that knowledge. Marketing ROI programmes are often discontinued because of expectations for results set within too short a timescale. Steady, stepwise improvement is the most successful approach to the art and science of marketing ROI.
