Shidhartha Pati is an engineering manager with CDK Global, leading the Internal Data and Analytics group. His interests include data and analytics strategy and design thinking
“Lack of data is not the issue. Most businesses have more than enough data to use constructively; we just don’t know how to use it.” Bernard Marr, Analytics thought leader, couldn’t be more right.
The ongoing pandemic has accelerated the move towards the digital. To survive and thrive, enterprises must leverage their data assets to extract meaningful and timely insights. The examples of how analytics is enabling digital businesses to stay competitive are many. This article talks about four areas where enterprises are aiming for analytic excellence.
Social Media Analytics
Social media has revolutionized how we communicate. Especially in these pandemic times, the usage of these platforms has skyrocketed. More and more people are getting online and spending more time to connect at a human level. Understanding the social consumers and what they feel about our businesses and brands has become critical.
Most of the social media platforms provide built-in analytics to understand comments, shares, likes and the user engagement. However, it is the integrated view across multiple social platforms that is more important. Recent advances in NLP and Sentiment analysis have made it easier to mine the social interactions to understand user opinions and feelings. Social data can be a rich source of information to understand how customers value the brand compared to that of the competitor.
And as any digital marketer would tell, social media analytics can be overwhelming and time consuming. There are many metrics to track – followers, page likes, impressions, reach, engagement rate, click-through rate (CTR) etc. Focusing on the few KPIs that matter the most can make all the difference.
Mobile App Analytics
Usage of mobile apps worldwide has reached new highs with 4.9 billion users and 8.9 million mobile apps. To provide a delightful experience to the users, businesses need to take advantage of mobile app analytics.
The first step is to build the funnel – how many people are downloading the app, signing up, engaging with the app and making purchases. The key metrics are new devices, active devices, sessions, session length, average time / device. These can provide actionable intelligence to understand customer behavior, segment the audience and improve the product. Mobile advertising is around 70% of the total digital advertising. Insights into the user journeys, what brings them to the app, what features do they most interact with becomes critical.
Marketing Channel Analytics
“50% of all marketing spend is wasted, we don’t know which 50%”, goes the adage. Understanding which of the marketing channels are the most effective and profitable is vital. Digital marketing gets most of the mindshare, so often the focus is on online marketing channels like paid search, email and video.
However, marketing is all about connecting with the customer at multiple touchpoints. A user conversion on the mobile app could have been influenced by that glossy ad in the local magazine. Offline marketing channels, such as billboards, direct mail, cold calls, print advertising etc. can’t be written off. Making the connection between online and offline is important.
Performing integrated analytics, possibly by adding a QR code with a trackable URL or a coupon code, can provide the aggregated view of the omni-channel landscape. Other marketing tactics, albeit controversial, are using infrared sensors in the shopping aisles or using video cameras to track customers.
Speech Analytics
Speech analytics analyzes calls coming to customer contact centers in real-time. It provides intelligence to improve customer experience, better meet customer needs, support business and product development decisions.
In a traditional customer contact center, only around 2% of the calls are analyzed to take corrective actions and spot non-compliance. NLP and AI powered speech analytics make sampling unnecessary. All the calls are analyzed in real-time to provide speech translation and keyword recognition. The call transcript is passed on if the call gets transferred. Sentiment analysis, recommending the agent the next action to take, suggesting knowledgebase articles improve efficiency. Supervisors get a real-time view of the contact center and analyze call metadata to better the support team’s performance.
We truly live in a data rich world. Technological advances in Big Data, AI and Deep Learning are making it easier for the decision makers across all functions in an enterprise to drive their business strategies with data driven insights.