Don't forget to do your cross-channel analytics!
Andree Bates
Eularis
We get a lot of enquiries about measurement of eMarketing activities such as eDetailing or social media marketing – which is fine as analyzing one channel in isolation is certainly better than not measuring any - but far greater gains can be made from cross channel analytics. In fact, the majority of our work is cross channel which means analyzing the impact of all sales and marketing channels – both traditional and eMarketing.
Cross-channel analytics enables a marketer to measure the impact from various channels in isolation and to compare the relative impacts of each, as well as measuring their impact in combination as part of your overall marketing mix. Various channels, such as websites, social media initiatives, eDetailing, customer service, phone support, journal write-ups, advertising, PR, meetings, congresses, patient support programs, investigator sponsored studies, sales force activities and programs and print media, to name a few can be identified, to understand how those channels relate to one another and affect customer behavior.
The most effective cross channel analytics enables one to predict the impact of varying levels and content of different channels together to see the impact these have synergistically rather than simply boosting the impact from one channel alone, facilitating scenario planning across a brand or portfolio of brands.
Pharmaceutical marketers utilize multiple channels of marketing communications simultaneously and need to be able to analyze the relationship between changes in different channels on the end result. For example, when a marketer implements a multichannel campaign, they will want to analyze the relationship of the different marketing channels on prescribing behavior.
"…analyzing one channel in isolation is certainly better than not measuring any - but far greater gains can be made from cross channel analytics."
By using cross channel analytics, one can adjust aspects and frequency and spend on different sales and marketing activities to see what the impact would be on overall sales and profit if we move x% of effort into eDetailing and take y% of effort away from rep calls, at the same time as decreasing our advertising and increasing our PR activities for example. What if we leave the advertising and PR and just reallocate the sales force alone? All can be uncovered using cross channel analytics. What about if we increase one component but leave the others as they are? This predictive interactional modeling is important.
Identifying cross-channel synergies requires looking at how different elements of the communication mix work together to move someone to prescribing or using your product. This does gain a greater level of complexity when a marketer implements a multichannel campaign designed to affect both online and offline impact, and then wants to analyze the relationship between online and offline behavior across all the traditional and e-channels. However, with data in so many locations, doing cross-channel analytics can be tricky without a system for measuring like with like - apples and apples if you will.
You'll need models that go beyond Web and social media analytics, and models that tie neatly into traditional sales and marketing analytics, but move well beyond the control and study group ROI approaches, and even beyond the traditional response curve approaches.
Web marketing teams utilize analytics that focuses on visitors' behavior, whereas cross-channel analytics tracks behavior across all channels to understand your customers experiences, their driver channels, and actions as well as the resulting impact on your sales and profit.
"Cross-channel analytics can make your marketing-mix models more effective because you will have a better understanding of the relationship between the different marketing channels..."
By using algorithms from both digital and traditional channels, you will be able to understand sales (and profit) impact based on changing sales and marketing activities content and levels different channels simultaneously.You will be able to predict revenue impact associated with changes in the communication mix, which can be used, for example, to make adjustments to content of an eDetailing campaign or spend in advertising.
Cross-channel analytics can make your marketing-mix models more effective because you will have a better understanding of the relationship between the different marketing channels and will no doubt improve your use of decision optimization tools to determine the combination or sequence of messages to maximize engagement and sales.
The implications of cross-channel analytics
Because customers today can move across several channels in the process of making a single prescribing decision, marketers are deploying cross-channel marketing and leveraging every communication channel. Successful cross-channel marketing requires a sophisticated analytics solution that can help marketers analyze customer behavior, make customer-centric decisions, and respond quickly to marketing opportunities.
Cross-channel analytics is going to require companies to invest more in acquiring and analyzing data to produce true insights and recommendations that are valuable to the business, but if the data is digested and utilized appropriately, then the cost is negligible compared with the return. For example, a recent large Pharma company spent $3m on a sophisticated analytics program that was able to identify the optimum cross-channel marketing mix across their entire product portfolio. This was demonstrated to lead to an increase in sales of $298 m within 6-12 months, with no additional increase in budgets, simply by reallocating spend to those channels that had been proved to drive share with the correct combination of programs.
"…with data in so many locations, doing cross-channel analytics can be tricky without a system for measuring like with like - apples and apples if you will."
As the need for whole-business analysis (and cross country whole business analysis) increases, marketers will need tools and models that bridge online and offline data with ease.
The ability to overlay many complex layers of data to generate a holistic view of customer behavior and campaign effectiveness has numerous implications for marketing professionals, from improving analytical skills to improving data quality to investing in better tools.
Marketers are going to need to embrace statistics, modeling, and predictive analytics in order to generate the potential returns that they dream about. Fortunately there are many tools available to help marketers do this without the need for comprehensive knowledge of the subject that are user-friendly while being powerful and effective.
About the author:
For more information on cross channel analytics and to view demos of this in action, contact Dr Andree Bates of Eularis http://www.eularis.com
Do you do your cross channel analytics?
