As mobile and social are quickly becoming new channels for customer acquisition, engagement and service, many brands across the board are looking to social and digital channels as a way to increase their customer knowledge and understanding through multiple customer touch-points.
As the use of social channels increases exponentially, it is critical that brands are able to create a 360-degree customer view by aggregating data from each one of these interactive channels. Without drawing from all touch-points, brands fail to have a holistically understanding of their consumer and run the risk of presenting disjointed messaging to their consumer as they visit the brand from a diverse number of channels.
Despite the availability of brand monitoring tools (e.g. Radian 6, Alterian and Scout Labs) and brand analytics tools (e.g. Crimson Hexagon, Crowd Factory, SAS and Oracle), brands face the challenge of trying to close the gap between aggregating data from diverse channels and drawing actionable business insights. In order to turn observation into business advantage, feedback mechanisms need to be created to channel insights towards product improvement, business process improvement and trend recognition.
Harnessing the power of big data to drive business and organizational decisions is not without challenges.
Real-time analytics: Recent statistics demonstrate how high the volume of Twitter data really is – Twitter is seeing around 155,000,000 tweets per day, at about 2500 bytes on average for each tweet and about 35 Mb per second – handling the immense amount of data at a sustained rate is a challenge. Also, gathering real-time analytics is made more difficult because of signal-to-noise ratio. Twitter is especially hard given the high rates at which tweets are created and the minuscule number of those tweets that are relevant to a campaign.
Sentiment Analysis: Sentiment Analysis is about the meaning of the content. Knowing the sentiment (positive, negative or neutral) is a good start, but not enough. The data needs to be analyzed to derive improvement opportunities such as ideas for product innovation and business process improvement. The process of mining data is additionally difficult since the human interaction component cannot be completely eliminated.
Many companies are trying to get hip on how to tackle the problem of harnessing excessive amounts of data spread across multiple customer touch points. As companies mature their social programs, they can progress through a variety of stages. Companies who are in the earlier stages of social maturity such as Gatorade are focusing their efforts on listening. Gatorade has created a “mission control center” which is staffed by employees who monitor Twitter and Facebook, 24 hours a day.
Other companies such as SAP have long been monitoring and interacting with their employees and customers via social community sites. SAP’s Senior Vice President Mark Yolton has spoken extensively about his 8+ years of experience using the Social Monitoring tool Jive, which has helped SAP form several social communities both internal and external to the company. The SAP Community Network is used to drive social innovation, commerce, intelligence and social insight. Mark champions that biggest benefit SAP has gained by creating these communities is around ‘Customer Intimacy’ – aggregating and analyzing customer data that allows them to create a 360-degree view of their customers wants, needs and actions which helps SAP understand and interact with more effectively.
At the more experienced end, are companies like Dell who use media channel to engage with consumers and drive sales. Dell has more than 9000 employees trained in social media, a ‘Chief Listening Officer’ and a twitter handle @DellCares which resolves 98% of Twitter reported support requests. Dell’s BI solution is available on a smartphone or tablet, provides up-to-the-minutes sales data and customer intelligence and suggests next actions for front-line service personnel.
The analysts at Forrester have coined a term ‘Social Intelligence’ which is defined as the process and use cases for harnessing social media data to inform your business strategy. It involves monitoring social media, collecting and analyzing the content, and using the insights to inform your strategy.
The true benefit of aggregating structured data (weblogs, social CRM, application data) and unstructured data (social applications such as Facebook, Twitter, LinkedIn, customer comments and product reviews) is being able to derive actionable insights. Additionally brands need toprovide a feedback mechanism to channel these insights for product improvement, business process improvement and trend analysis.
Aggregating and analyzing data across channels provides the following additional benefits:
Identify New ‘Niche’ Customer Segments – Just because people share some similar characteristics such as age and gender (e.g. female in the age group 35 – 45) does not imply that they share the same passions and interests. Building a community of loyal followers, deeply engaging with them and actively listening and participating will help to identify new niche customer segments.
Deliver Targeted, Personalized Content and Advertising – The future of competitive advantage lies in managing and analyzing all the critical data entering a business environment. Data which provides user preference and location information such as product reviews, check-ins, ratings etc. collected across the mobile, social and digital channels provides a wealth of information for improving customer understanding and targeting them with personalized content.
Increase Customer Loyalty – Customer loyalty and satisfaction can be improved by creating a 360 degree view of the customer and gaining deeper insights into existing customer segments as well as discovering new customer segments by developing a multi-channel strategy and aggregating data across mobile, social and digital channels.
Drawing business insights such as determining ‘top performing regions’ or ‘top influences’ can be accomplished relatively easily by aggregating and analyzing structured and unstructured data, however, the hard part is in drawing subjective business insights such as determining ‘product improvement ideas’ or ‘future trends’.
The key to successful subjective analysis is in empowering and training the personnel at various customer touch points to ask probing questions of customers and flag answers which require deeper analysis. Flagging specific ‘key data points’ will allow actionable nuggets of information to be highlighted and stand apart from the sea of information.
Additionally, forming a deep relationship between people interfacing with customers at multiple touch-points such as social media channels, customer service channels, websites etc. and subject matter experts, such as product managers and designers who are within an organization, will allow for business insights and relevant data to be captured in ‘real-time’ rather than ‘after the fact’, which will lead to better understanding of customer behavior and opinions.