Content shock, social avalanches, data deluge – pick your phrase du jour. However described, PR and Marketing is awash is data. It would seem logical that communicators would rush to embrace data as a strong asset in defining and refining strategy for better outcomes. And yet many prospects and clients are stating that they only need data on “core” (aka traditional) media and social media effort. Some are still only asking for share of voice as their core PR metric. This mindset ignores more cutting edge analysis such as customer journeys, and even more “traditional” marketing funnel aspects related to PR.
The question is why? In the days of Google Analytics, IBM Watson and Tableau, why are communicators still afraid of data?
Leaving untapped data on the table not only ignores the best practices, it’s also severely limiting. There are signs that in the near future PR and Marketing teams will need to embrace and understand even MORE data – data that lies outside of their silos in ERP, CRM and other systems.
There’s a few possible reasons why:
Data analysis skills, starting with Excel skills and moving beyond to basic statistics for things like standard deviation, are not in the humanities/English major toolkit. Career entrenchment and lack of understanding are powerful motivators to resist change.
Data could uncover underperformance in key areas or significant blind spots that PR and Marketing “should” have identified. Better to not know than to expose failure.
Lack of senior leadership endorsement/pressure
This is likely the major factor in why adoption of data techniques across PR and Marketing is slow and/or nonexistent. Most C-level leaders are looking at financial metrics alone, and are not motivating internal teams to go beyond checking the box on top line metrics such as number of followers or SoV.
This mindset will be very outdated in the very near term. Consider three seemingly unrelated news events from July 2016.
- Google debuted two natural language tools to help businesses develop AI software. This is direct move to a) democratize access for non-IT developers to tap into AI and b) motivate businesses to think more deeply about how they can leverage Google’s data – which Google will likely happily charge a subscription.
- Facebook now has the world’s top three applications with Messenger hitting the 1 billion user mark.
- IBM announced a partnership with Macy’s to leverage IBM Watson for an AI driven mobile personal shopping experience.
And while it might feel like Facebook and Google have already won the AI race, with the largest global user bases and search data repositories respectively, it’s actually just starting. At the recent Fortune Brainstorm Tech David Kenny, general manager of IBM Watson, laid out a clear opportunity as part of the AI roundtable.
“‘Data will become a currency,’ Kenny said. He also explained that only 20% of the world’s information is stored on the Internet, with the other 80% being privately held within companies and organizations.”
If 80% of data is within organizations themselves, applications like Slack are primed to be the place where data is exchanged in an enterprise vs. a Facebook or Google. Applications from these vendors and others will push cross team and cross department collaboration, surfacing the need to share data alongside documents for better context, use and ROI.
This sharing could be incredibly powerful if harnessed correctly. For example, consider the following possible use case.
- Certain call center messaging and social media posts are shown to increase customer loyalty, and even identify new pain points that could be productized.
- Marketing reviews the data, and leverages the insights to refine and optimize social media, content and SEO to match those needs to create demand in the base.
- The outbound messaging creates measurable demand for the new services, which feeds into the CRM system. Marketing reviews the CRM data to understand what channels performed best and what features are most requested.
- Marketing then feeds that data with real-world demand metrics to help R&D refine the product set and get it into market more quickly.
- In concert with A/B message testing, Marketing helps customer service predict customer questions and develops materials to more quickly and easily resolve issues.
- Marketing measures customer satisfaction ratings and feeds revenue projections into the ERP system, which drives bottom line results and ROI.
The amazing part of this example is all of the necessary data lives in systems and tools today. PR and Marketing not only need to step out of existing comfort zones regarding its own data – it needs to embrace the potential role of being the data hub of company strategy. Start by embracing skills long forgotten or unlearned, begin asking more questions of your Google Analytics data, and start visualizing data across your own communications silos. This will set the baseline best practices to enable incorporating even more data across your organization and turn Marketing and PR into a longer term strategic business partner.