Historically, online and offline data have been relegated to separate silos. The combination of a variety of KPIs from different media entities has made breaching the walls between these silos incredibly difficult. The always-on nature of mobile technology combined with the growing power of the consumer’s voice across online portals has created a perfect storm designed to smash the silos between customer survey data and the quant/qual data that consumers post 24/7 across social media, blogs, and forums.
While both consumer survey data and social media conversations provide unique and meaningful insights to businesses, the two are not frequently intertwined to leverage their combined power. As new and innovative technologies are introduced, it’s become possible to compare industry standard metrics across platforms and disciplines. Synthesio, in partnership with valued client ANZ Bank, has aligned the traditional survey metric, Net Promoter Score (NPS) to the proprietary social metric, Social Reputation Score (SRS) in a study which asks the question, “Do customer satisfaction results from paid surveys about Financial Services brands correspond to the sentiment that consumers express online during the same historical period?”
The comparison of two different metric sets from two disparate disciplines presented a significant problem that needed solving before granular data analysis could begin.
Customers who take to social media to advocate or denigrate a brand typically post “in-the-moment”, as a result of an emotional cue. Survey responses are often divorced from these emotional cues - as they generally take place after respondents have a chance to cool down and view things more objectively. In addition, social media users are not limited in their range of vocabulary and sentiment - whereas, survey respondents are locked into predetermined choices that might not fully capture their thoughts and feelings.
In consultation with ANZ Bank, Synthesio’s analysts formulated a strategy that was driven by three key pillars designed to smash the silos between datasets:
- Lag Time: Determine an approximated lag-time delta to more accurately layer collected survey responses onto a social media mention timeline
- Keywords: Determine which target keywords from survey verbatim would be “matched” to social listening queries so topics could be more accurately correlated
- KPIs: Synthesio’s Social Reputation Score (SRS) naturally matched to Net Promoter Score (NPS), but could additional KPIs be layered into the results to provide context beyond sentiment?
In order to better understand if possible correlations exist between two disparate data sets, one must first understand the two populations from which the data comes from and then look visually at the comparison of the data streams to determine if a possible linkage and/or similarity exists.
Synthesio, an industry leader in global listening capabilities, has developed its proprietary global data aggregation system on a truly global level.
We concentrated our study on a comparison of our proprietary customer satisfaction metric, Social Reputation Score (SRS), with the industry standard offline KPI of Net Promoter Score (NPS) during the period between October 2015 through June 2016. Our analysis demonstrates how the Net Promoter Score calculated from the online survey results has some similarities with the Synthesio Net Sentiment Social Reputation Score (SRS). Also, when re-calculating the SRS to mimic the exact calculations of the NPS, the correlations become even more evident. We were able to show how the correlations were further validated using qualitative conversations to pinpoint trends to the ebbs and flows of the bank’s NPS score. A boost in both scores was achieved when ANZ launched digital promotions and sponsorships and similarily, negative press mentions caused declines in both scores. In addition, there were keywords within online conversations that displayed linkages to survey questions related to brand reputation, purchase intent, and customer satisfaction.
Join us at NEXT on May 9-10 in New York, where Margie will disclose the full details of this study and demonstrate the power of combining online real-time data and offline stated data.