5 More Ways to Improve Your Marketing Program In the first installment of this article, we looked at some straightforward approaches to improve decision making about marketing resource allocation. In this second part, Ill draw from the best practices in organizations of all sizes to expose some additional opportunities for marketers today. 1. Capture Fragmented Spend in New Marketing Mix Models Marketing mix modeling once was the preserve of only consumer packaged goods (CPG) marketers with big advertising budgets. Today, our most sophisticated antenna, employed with the latest modeling techniques and huge amounts of highly fragmented data allow B-to-B marketers to benefit as well. One example: a global technology leader today is able to map—across the US and China—thousands of small B-to-B spends with thousands of small spends in specialist digital and print spots as an input, and thousands of customers and their transactions as an output. 2. Understand How Intermediation Is Evolving The best models capture the intermediated effects of marketing spend and how different marketing levers work. This can be seen in different ways. For example, automotive advertising might be intended to drive website traffic and dealer footfall in the short term that will be seen in stronger sales further in time. One TelCo company looks at how marketing spend drives Google queries, footfall in their stores, calls to the call center, traffic to their website, and ultimately improved retention and accelerated customer acquisition. The role of social media as an accelerant is also captured in these models, and marketing campaigns effects can be dramatically positively or negatively moderated by this intermediation layer of social media. Another example of intermediation is in the U.S. insurance market, where the traditional agent-based business model has come under threat of Web-based aggregators or direct business models. The way in which intermediation is changing from agents acting as a layer between the advertiser and the consumer, and now a more direct relationship, has to be tracked and optimized. There are huge marketing optimization opportunities in this space of changing and evolving business models in financial services, and of course, in retail. 3. Meta Models Include Many Separate Models and Research Youll now be faced with so much research, Web-focused analytics, traditional marketing mix models and so on. But, theyll all be telling you a part of the story in isolation. Meta models can include multiple vendors models and research in a single business simulation tool. One example is a 10-year, $2 trillion simulation for a U.S. retail gasoline company. This employs strategic models and tools to analyze marketing decisions with a long-term focus, often using customer-level CLTV models to analyze the impact of marketing at the customer level. Agent-based modeling uses similar techniques in computer games to build populations of customers, each with attributes that match real consumer behavior helps us create meta models that look at the long-term outcomes of marketing spend. A marketing mix model is no longer a single regression equation. Its a flexible system that can include multiple inputs from all your various sources of research, insight, and analysis. 4. Create the Right Infrastructure to Optimize Marketing Spend and the Use of Your People A variety of trends are driving this, including some of the points we made above, e.g.: The ability to manage ambiguous answers from multiple data. The creation of meta-models that join models and analytics, often from multiple vendors and in-house capabilities. The dissolving of the analytics department as capabilities become more entrenched with marketing. More marketers will be ready and able to do more of their own analyses with desktop tools. New data for driving strategic marketing decisions will be embraced by marketers. What does this mean for marketers? First, old department structures are outmoded when analytics tools can be embedded in the marketing team, not as a stand alone analytics resource isolated in the basement. Second, the organization and analytics/insights function at corporations has to change because consumers are changing. Trends like e-commerce, the rise of mobile, big data, and omni-connectivity change what we need to know about customers and their behaviors. Third, businesses are changing their business models, e.g.: more E-commerce, brand-partnerships, and thats leading to a shift in what they need from analytics/insights resources—the people, processes and tools. 5. Sustain Test and Learn Programs Over Time To illustrate the power of sustained test and learn programs in marketing, I want to turn to an analogy I often use of Formula 1 auto racing. Think about F1 auto racing—the global zenith of motor sports. Teams add new parts to their racecars in succession (a better front wing, improved exhaust, a more efficient diffuser, and so on), with each new component adding a tiny improvement to their cars lap time, but collectively and over time, giving a big improvement in performance. Over a nine-month season, hundreds of new parts will be tested, each potentially cutting only a hundredth of a second off a lap time. But cumulatively by the end of the season, it may have gained the car several seconds of extra time. In the same way, marketing affords many opportunities for performance improvement by aggregating small improvements. Small incremental improvements across marketing effects of acquisition, retention, spending and so on, combine to create a cumulative large improvement in performance. To move forward overall, there has to be systematic testing of new components. This is how F1 teams get faster, by testing many new components, each of which give a small incremental improvement. And to find a new part that makes the cars go faster, sometimes teams need to test a part that makes the car go slower. Testing new car parts is how the teams move forward, but because its only possible during a race weekend, it carries the risk of actually damaging their performance when it matters most. Always instigate a formal test and learn program with multivariate testing of audience targeting, media mix, messaging, use of social media and advertising etc. Flex the risk profile of the test and learn framework, depending on business performance. But there are two aspects to this as takeaways: 1) test and learn disciplines are the only way you get to figure out whats working and for you to optimize your budget sizing and allocations, and 2) you need to do this patiently and systematically over time. This is how marketing leaders have achieved the greatest gains in marketing optimization.
Posted on: Sat, 01 Feb 2014 08:42:20 +0000
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