Power marketers are always interested in the most effective ways to track, measure, and analyze customer experiences for more relevant engagement. I’d like to share an approach that is less known yet potentially quite powerful.
Businesses across global markets are re-thinking data, analytics, platforms, and research methods to better understand their customers. Event analytics offers a new view of the customer, leveraging best technologies and diverse data sources, to obtain actionable insights in real time. Traditional methods help us understand consumers in terms of the following aspects: who, what, when, and where. Yet two of the most important questions for understanding consumers (“why” and “how”) are un-answered. The answers are key to obtaining business value because they can help us understand the why and how of consumers’ interactions with a company.
Traditional approaches focus on how the customer looks to the business. For example, what do you buy? What segments are you in? When was your last visit? However, the more important question should be “how does the business look to the customer?” How do our customers experience our products and brands? How do customers feel at each touch point?
One major advantage of event analytics over traditional methods is that it can improve our understanding of the customer’s view of the business. Traditional systems are not designed to solicit, extract and stitch together customer experience data well. Event analytics obtains information about the entire customer experience in detail, threading together many sources of information from different applications that combine to deliver the full view of customer experience.
To conduct event analytics, businesses need to create a “customer experience universe” that stitches customers’ experiences together, allows for easy behavior pattern recognition and facilitates visualizations of customer behaviors. This universe includes social media, customer experience, marketing channels, mobile apps, and devices. Then, machine learning algorithms are used to run through all the data to identify patterns.
Event analytics is an ecosystem that includes, for example, streaming ingestion of events, event repository, event metadata, guided user interface for business analysts and machine learning algorithms. One category of use cases is called funnel analytics which help us to understand customer behavioral patterns and what triggers their experiences.
Funnel analysis provides visibility across a series of customer experience events that lead towards a defined goal, say, from user engagement in a mobile app to a sale in an eCommerce platform. Funnel analyses are an effective way to calculate conversion rates on specific user behaviors, yet funnel analytics can be complex due to the difficulty in source categorization, visitor identification, pathing, attribution and conversion.
Funnels can be built using a single guided user interface without needing to write code or move data. As a result, event analytics can scale at the speed of business. It is a smart analytic approach because it helps create visibility to the path that users are most likely to follow to achieve their goals.
The value of having this insight is of great significance since it gives marketers a deep, data-driven line of sight into the customer experience universe.
James Semenak is a Principal Consultant with Teradata – known as an evangelist and architect for Event Analytics as well as Big Data Analytics and strategies. James consults in all things related to data and analytics around the internet, and has worked with Shutterfly, Expedia, eBay Enterprise, Charles Schwab, Nokia, eBay, PayPal, Real Networks, Overstock.com, Electronic Arts, and Meredith Corp.