In our rapidly evolving world of marketing analytics, especially with the daily articles on “Big Data” streams, predictive analytics and real-time reporting, many of us forget to consistently apply the basics we’ve learned from our research and analytics.
One core basic that I call “context” provides the needed focus. Context enables a strategic view that is necessary for effectively and efficiently planning, executing, reporting, and then acting — in other words, for charting the shortest distance from data to insights.
But first a little context on context and insights. Recent surveys of CMOs and other C-Suite executives continue to emphasize the top priority placed on gleaning actionable customer insights (e.g. McKinsey & Company’s “Minding Your Digital Business” report from May 2012).
Additionally, most marketers report their corporate management is now more likely to invest in the necessary technology and data assets to obtain deeper insights into consumers’ attributes, behaviors, mindsets, etc. to enhance the performance of their marketing programs, according to a CMO Council report.
Research Must Inform Go-to-Market Decisions
These corporate and marketing executives are seeking actionable insights that provide material business value by informing many of the following key go-to-market decisions, among others:
Target Audiences – What target audiences provide the best opportunities for my brands?
Brand Positioning – What point of differentiation offers the most appealing and viable positioning?
Creative Expression – Which creative expression has the best strategic fit and is the most compelling?
Media – What media or mix will be most effective and efficient in reaching and engaging?
Campaign Performance – How are my campaigns performing and which metrics should be optimized?
To many readers, I am sure this all seems quite sensible and elementary. However, I continue to see reports (and have clients who mention reviewing reports) that deliver lots of data but no real insights, especially actionable insights that provide material business value by informing many of the above-mentioned go-to-market decisions.
Collectively these reports appear to lack the focus that context can provide, from planning to analysis to reporting, or from data to insights to actionable recommendations.
Use Context To Focus Your Efforts
If we look at the very definitions of the term “insights,” either based on logical thought or intuitive processes, they emphasize the importance of context and focus. Here are just a few examples:
Understanding a specific cause and effect within a given context
Identification of relationships and behavior within a model, context, or scenario
Selective encoding, selective combination, and selective comparison
Gestalt — seeing the bigger, coherent picture of a problem
Hypothesis — linking data which had previously seemed unrelated
Insights are derivations of rules — mind models for predicting outcomes
Among these, hypothesis testing provides a special context or conceptual framework for focusing our measures and assessing the probability of our observations. It lets us reject the improbable null hypothesis (e.g. no difference…or not causal) and accept the alternative hypothesis (e.g. different, greater or casual in proper experimental designs).
In this regard, insights are most effective when they either confirm or directly challenge your mind models, and, in turn, create disequilibrium and motivate decisions and course corrections. Clearly we need insights to deliver real value to prospects and clients.
Starting With the Client Context
Ideally, all marketing research and analytic initiatives should start with a solid “client” context, which should provide the conceptual framework and focus for informing our planning, executing, and reporting — including the clarity of our recommendations based on actionable insights of material value.
Again, this is quite sensible and elementary, but I continue to be amazed by reports and presentations that do not provide or repurpose this client context in terms of a brand or campaign brief. The frequent consequence is that the analytics plans, reports, and discussions are inefficiently voluminous and circular, and ineffective in informing specific client decisions.
These client, brand and campaign briefs do not need to be lengthy. In fact, they should be brief yet provide the necessary conceptual framework to guide our research and analytics value chain. These briefs should provide a short summary sentence or two on each of the following, among others:
Purpose or Objectives
Brand building, performance or both?
Specific decisions the client is making in light of the research or campaign analysis
What information or metric do they believe would be most useful for informing their decisions?
Prior benchmarks and distributions
Marketing Strategy
Market structure, especially in terms of competitive set, relative positions and target segments
Target segment definitions and category appeal, purchase cycle, etc.
Brand positioning, appeal, equity or challenges
Media Strategy
What media or mix will be used to reach and engage?
Weight and results in prior campaigns
Single channel or multi-channel attribution
Targeting criteria
Timing & Geography
Buying method
Budget
Creative Strategy
How does the creative express the brand strategy?
Different versions for different segments?
Are their calls-to-action? Offers?
Campaign Performance
What is key objective and key metric?
Performance standard, baseline, or “allowable” cost (engagement, lead, customer, etc.)
This type of information contained in a short client, brand or campaign brief will, as mentioned, provide the researcher or analyst the conceptual framework for efficiently designing, executing, reporting and making clear recommendations. This approach will naturally lead to the data case, including visualizations and relevant insights, that supports clear action-based decisions with material business value.
Effectively Putting Data Into Context
Further, within the report or presentation, It is highly desirable to put the data within context, which helps to reveal both relative efficiencies or response likelihoods, as well as relative size or materiality. For example, Chart 1 below shows an audience and responder profile based on Mosaic Social Group segments for a recent display campaign. Percents and index values are displayed for both audience impressions and click-through responses.
Chart 1: Audience & Response Profiles
Both Percentages And Index Values Provide Necessary Information
For the audience analysis, the percentages, of course, represent the relative number of impressions across these segments, while the index values reveal the relative efficiency of the media buy in targeting these segments (Where audience segment index value = % Impressions/% US Adult (18+ years) Population X 100; 100 represents random/untargeted…and 200 represents 2X media efficiency). Thus the audience index values provide context for the percentages by revealing the relative efficiency of the media buy in targeting specific segments.
Similarly, for the responder profiling analysis, the percentages, of course, represent the relative number of responses across these segments, while the index values reveal the relative likelihood to respond, given the opportunity to respond.
In this case, the segment response index values are derived by indexing against the impression audience (where response segment index value = % responses/% impressions X 100; 100 represents average response likelihood…and 200 represents twice as likely to respond). Thus the response index values complement the segment response percents by providing the context for determining the relative likelihood of consumers in each segment to respond, given the relative opportunity to respond.
Collectively, these audience and response profiles, shown with percentages with index values, provide data and visual context, to easily make and communicate very specific media recommendations, such as:
Reinforce – American Diversity & Varying Lifestyles
Increase – Upscale America, Affluent Suburbia & Aspiring Contemporaries
Reduce – Small-Town Contentment, Metro Fringe & perhaps Urban Essence
This same set of audience and response profiles can also be visualized into insights quadrants (Chart 2) to further reveal and enhance communications about both relative efficiencies and relative likelihoods, as well as target discovery, and, in turn, how to best revise the media targeting and buy to enhance both media efficiency and consumer engagement.
Chart 2: Audience & Response Insight Quadrant
These are just two examples of reporting data within context, which aids in telling the full story. It’s important to remember that percentages by themselves convey relative amount, but do not speak to the relative efficiencies or relative likelihoods. Meanwhile, index values by themselves convey these relative efficiencies or likelihoods, but do not reveal materiality, importance or size of the opportunity.
My humble goal for this article is to speak to the value of context — client context and data context — for charting the shortest distance from data to actionable insights or material business value. I aim to do my small part to reduce the likelihood that readers will review reports or view presentations that fail to produce meaningful results.
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