Nowadays, as every click is tracked, we no longer get to a web page by chance. Companies have understood this. They tend to want to bring their corporate communication and influence strategies closer to their marketing practices. The traceability of the sacrosanct “customer journey” and the exhaustive collection of generated data lead them to converge their practices and the tools at their disposal. On subjects that are something else entirely and sometimes even fundamentally different.
Companies are certainly able to know how many people were exposed to their content, but also how many clicked, shared, commented, watched (and for how long), giving to data collection a very important role in the construction of subsequent campaigns. From a theoretical global indicator, audience measurement has moved to a success prediction algorithm. Does this mean that the mathematical result of this equation must become the only empirical indicator of success? Nothing is less certain.
Marketing strategy and INFLUENCE strategy do not always meet the same objectives.
If in both cases, the interest generated towards the company or the brand is the major issue, the measure of its success sometimes differs. For a promotional offer, for example, the simple measurement of the number of views of an advertisement can meet the objective set before the campaign. For image purposes, and therefore for influence, measuring the success of the communication can and must be more subtle. The recent example of Nutella and Intermarché are a perfect illustration. The campaign proved to be effective, from a quantitative point of view, even beyond all expectations for the distributor, but damaging for its reputation and that of the Ferrero group, as its own spokesperson on the French territory admitted.
The marketing action is often a short term action, a “ploy” whereas influence requires a long term strategy.
Marketing action has a beginning and an end, a commercial objective and an immediate tangible result. Influence strategy, on the other hand, can only be measured over a longer period of time, by strengthening the findings of quantitative indicators with a more qualitative analysis. Who could have predicted, for example, at the time of the commercial failure of Apple’s Newton Message Pad in 1993 (and its communication launch campaign) that the Cupertino firm would be the most admired company in the world today?
However, the bridges between tools applicable and applied to marketing and influence campaigns are more and more frequent. The line between quantitative and qualitative indicators is becoming increasingly blurred. By creating reactions (instead of likes), Facebook has brought an additional reading grid to the perceptions of online publications. Brands can thus study the number of reactions (a purely quantitative observation) but also the quality of the reactions generated (“likes”, “anger”, “loves”, “laughs out loud”, “sad” or “astonished”), bringing a more qualitative dimension to the data collected. Semantic analysis software are progressing at high speed and should quickly offer efficient solutions, especially for content shared on the Internet. The change in Facebook’s algorithms, which favors the appearance on a profile’s timeline of content similar to that already liked by the profile in question, is proof that the all quantitative model (which favored the appearance of the most popular content in general) is no longer valid. It is adapting to the constraints and opportunities that technological developments and data processing bring.
Communications specialists, too, have to adapt to know how to measure success according to the type of campaign. As with any progress, data analysis and the exhaustiveness of indicators offer many possibilities but cannot, and should not, define a new way of functioning. It is up to how we use it to inspire the variants and opportunities. And particularly in communication, a field of human complexity and subtlety, probably even more than anywhere else.
In the field of brand image and influence analysis, the truth of a figure can only be revealed to those who take the time to study its outlines, its context and its subtleties. Algorithms give a truth, rarely THE truth. In our business, they cannot replace the human brain. The consultant must have the last word and is the only one who can ultimately answer the complexity of a communication situation that involves social, economic, political, psychological and emotional issues.
Hence the importance of thinking the measure more than measuring the thought.