Who Should Track Behavioral Analytics? Metrics to Measure Across Departments
By Megan Wells
Data-driven marketing is a phrase you’ll hear often as teams look to ever-growing stores of data for insights and epiphanies. There’s good reason behind the effort--companies that make business decisions based on data insights consistently outperform those that don’t.
On average, however, enterprises use only 50% of the information available to them for their decision-making process. That’s a lot of untapped potential--and not just for marketers. Vast datasets containing valuable information about customers in addition to employee-gathered intel can inform decisions across departments in your entire organization, including:
- Market research
- Information technology
- Customer experience
- Digital experience
- Product management
To combat the challenges of complicated tech stacks, disconnected data silos, and slow time to insights, organizations are looking to improve their behavioral analytics strategies. In this article, we’ll take a look at how various roles can overcome common analytics issues through the use of behavioral analytics management to help them make faster and smarter decisions within their enterprise.
Market Research Teams
Traditional market research methods such as surveys, interviews, and focus groups provide invaluable opportunities for understanding consumers, but they come with limitations. These methods are incredibly labor and cost-intensive, as they require active participation from the consumer or oftentimes costly industry reports.
Take, for instance, consumer focus groups. You need to find and recruit appropriate respondents, get their explicit permission, organize a venue (either online or in-person) and design the questions--all before the research even begins! This means data collection typically occurs after a purchase happens and relies on humans’ memories, which are often flawed.
Since behavioral analytics data is collected passively, it doesn’t require direct participation from the consumer. Thus, you can gather information much faster. Additionally, behavioral data is real data that are not skewed by faulty recollection.
Market researchers can create better survey experiences by using behavioral data to identify and segment the most appropriate research participants. In a study by the Pompeu Fabra University in Barcelona, market researchers sent the same survey to two groups of respondents: one randomly selected, and another that was selected based on behavioral data (specifically, their website interactions).
Using behavioral segmentation to identify research respondents produced greater success in:
- Survey completion: 89% of respondents from the behavioral segment completed the survey, compared to 46% for the random sample.
- Satisfaction: The behavioral cohort reported an 80% satisfaction rate with the survey experience, compared to 60% for the random sample.
- Data quality: Behaviorally-segmented respondents had fewer “don’t know” or incomplete responses.
Information Technology Teams
Gaining insight into consumer behaviors is one of the main reasons organizations collect and analyze data. But behavioral analytics is also a valuable tool for understanding employee behavior.
Given the growing threat of cyber attacks--IT teams can leverage behavior analytics to improve data security within the enterprise. Behavioral tracking of logins, endpoint activity, and network events can alert IT teams of inconsistent or suspicious activity. Find malware infections before they cause damage and take security measures quickly to stop a potential security breach in its tracks.
Customer Experience Teams
In the digital age, customer experience is a top driver of loyalty, and that translates directly to revenue. Research finds organizations that leverage consumer behavioral insights outperform peers by 85% in sales growth and more than 25% in gross margin.
CX teams can use behavioral analytics to:
- Evaluate the effectiveness of their self-service channels.
- Uncover the cause of low CSAT or NPS scores.
- Zoom in on the reasons for new client service calls.
- Reduce response time and total time to resolution.
- Anticipate and better serve consumer needs to boost brand loyalty.
Looking at the end-to-end customer experience through the lens of data, not assumptions, is your fastest path to improving your customer experience strategy. Just ask CX leaders like Ritz-Carlton, Singapore Airlines, and Uber.
Sales teams in SaaS, retail, and other industries use behavioral analytics to improve customer acquisition and boost revenue. Time is a sales rep’s most valuable resource, and customer intelligence tools can help teams identify, rank, and segment prospects based on their likelihood to convert to paying customers. With this information, sales reps know exactly where to prioritize their outreach and score the greatest revenue potential.
Sales teams also use behavioral tracking to target customers at key points in the customer lifecycle. For example, airlines and OTAs (online travel agents) may observe that customers tend to buy plane tickets in the spring and summer.
With this knowledge, sales teams can time offers and know exactly when to ramp up communications with customers, maximizing the ROI of their efforts. Companies like EasyJet, Travelocity, and Kayak can use lifecycle emails to:
- Retarget: Follow-up after a search that didn’t result in a purchase by offering a discount or similar items
- Upsell: Reach out after a ticket purchase to encourage seat upgrades and related purchases like hotel rooms and car rentals.
Digital Experience Teams
Digital experience analytics focus on the metrics surrounding how visitors interact with individual elements of your website or app. Beyond simply measuring entrances to your web pages, digital experience analytics is designed for behavioral deep dives. Understanding how users interact with every button, tab, and image, will inform your overall goals.
French travel company Pierre et Vacances used digital behavioral analytics to see that “number of rooms” was a preferred search filter on their site (based on high numbers of clicks and healthy conversion rates). In response, Pierre et Vacances made the filter more prominent by moving it to the second position among several filter options. Thus, the company discovered an easy way to increase conversions by making this popular feature easier to find.
Airbnb takes it a step further. The travel industry disruptor uses behavioral data analysis to personalize the layout of photos based on predictions about which images guests are most interested in, making them more likely to book.
Product Management Teams
What drives people from their freemium subscription to the paid version of your product? Why are you seeing a sharp drop-off rate at a critical step in the buyer journey? What key events or actions guide users to a point where they realize value from your product--and how can you get them there faster?
These are all questions that behavioral analytics can answer for product teams. Observing how people use (or don’t use) your product helps teams improve product features, increase customer retention, and reduce churn. Depending on your goals, behavioral analytics metrics for product management fall into a few different categories:
- Engagement metrics like average daily active users, shopping cart or checkout abandonment, pages viewed, or sessions per user.
- Retention metrics such as retention rate, churn rate, product or feature stickiness, and daily retention.
- Transaction metrics include average revenue per daily active use, customer lifetime value, and cost per acquisition.
The best behavioral analytics tool is the one that provides real-time insights across all users, digital interactions, and operational data. Only a robust, unified view can provide the context your organization needs to benefit your teams cross-functionally.
Want to see how Scuba provides 360-degree behavioral intelligence for a wide range of stakeholders, without added complexity or the need for deep technical expertise? Schedule a demo.
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