Data experts have repeatedly expressed the importance of switching from traditional outputs to business outcomes when building a data strategy. But when it comes to it, even measurement professionals are tempted to “do what is usually done” instead of creating objective-oriented solutions. Luckily, the plethora of data analytics tools available in the market unleashes various propositions to this rather simple question:
How do we build a holistic data strategy that directly links PR and marketing efforts to business objectives?
DATA (AND ITS EXPERTS) MUST BE OMNISCIENT FROM THE START
There are countless white papers, blog posts and conferences that discuss how important data is to both PR and marketing professionals. But few highlight the value and effectiveness of including data experts from the very beginning of every strategy-related conversation.
Too often, creative, marketing and PR teams acknowledge the value of measurement expertise only at the end of a campaign. This not only leads to missed opportunities to collect valuable data, but it also prevents teams from tapping into an extensive source of knowledge provided by the combination of human experience and advanced technology, including Artificial Intelligence (AI) analytics. Allison+Partners advocates for the need to leverage creativity with science, already at the disposal of people who know how to analyse and translate it accordingly. Its Performance+Intelligence team is composed of data and research experts from various backgrounds across the communication industry, dedicated to guiding strategy upfront and carrying it through to measurement.
CONTEXTUALISE IMPRESSION
In communications measurement, impressions are a data point that indicates the potential number of users that viewed a piece of media. In paid and earned, it is desirable to generate as many impressions as possible, as it aims to measure the extent to which an audience was exposed to said piece of content. But exposure doesn’t equal consumption. Thus, impressions are not enough to guarantee that a brand feature reached the eyes – and the brain – of a reader. Adding tailored impact measures as a performance metric could help bridging that gap. Did it include a picture containing the brand’s logo or the product being promoted? Was the link towards the brand’s website added in the editorial space? It is proven that people spend less time scrolling through online and print media. Supplementing impact measures to impressions evaluates PR results with more precision and adds actionable insights for the PR teams.
CROSS-PLATFORM ANALYTICS AND VISUALISATION
We know the customer journey is not linear. For data experts, it means that measurement strategies don’t have to be, and communicators should supplement traditional metrics to uncover potential impact. For example, earned media tends to rely heavily on the traditional ‘volume-readership-sentiment’ trio to evaluate awareness. But we can associate other KPIs as a best practice to measure success beyond reach: did that media article lead to an increase in website traffic? How many social mentions and hashtags appeared on social media compared to the week prior to said article? With time, comparing high and low-performing earned efforts across media and social metrics will unlock key patterns that will provide valuable insight.
Similarly, data structure and visualisation should reflect these cross-platform analytics while answering that main question as simple as possible: How do we attribute business results? To build robust and sophisticated measurement strategies, A+P uses the most advanced AI and Machine Learning (ML) tools and platforms on the market.
As we head towards 2022, it is essential for marketing and communications leaders to reflect back on past projects and create new opportunities to build successful strategies for the future. This can be done by setting up objectives together with data and measurement teams, tying data collection to customer actions as often as possible, and unlocking actionable insights through complete, multi-channel measurement frameworks.