Use Case: Customer Analytics
The Business Challenge
As a CMO, digital marketing, or customer loyalty executive responsible for optimizing customer acquisition and loyalty campaigns, you need greater visibility into the customer buying journey. Why? Because deeper, data-driven customer insights are critical to tackling challenges like improving customer conversion rates, personalizing campaigns to increase revenue, predicting and avoiding customer churn, and lowering customer acquisition costs.
But consumers today interact with companies through lots of interaction points – mobile, social media, stores, e-commerce sites, and more – which dramatically increases the complexity and variety of data types you have to aggregate and analyze. Think Web logs, transaction and mobile data. Advertising social media and marketing automation data. Product usage and contact center interactions. CRM and mainframe data. And even publicly available demographic data.
When all of this data is aggregated and analyzed together, it can yield insights you never had before – for example, who are your high-value customers, what motivates them to buy more, how they behave, and how and when to best reach them. Armed with these insights, you can improve customer acquisition and drive customer loyalty.
Increased customer conversion by 60%
Improved targeted advertisement resulting in $1.65 million in savings
Reduced customer acquisition cost by 30%
Increased revenue by $20 million
Why Big Data Analytics?
Big data analytics is the key to unlocking the insights from your customer behavior data – structured and unstructured. It empowers you to combine, integrate and analyze all of your data at once – regardless of source, type, size, or format – to generate the insights needed to drive customer acquisition and loyalty.
For example, imagine being able to use insights about the customer acquisition journey to design campaigns that improve conversion rates? What if you could identify points of failure along the customer acquisition path – or the behavior of customers at risk of churn so you could proactively intervene and prevent losses? How would it help if you could understand high-value customer behavior beyond profile segmentation (for example, what other companies they shop from, so you can make your advertisements even more targeted)?
Datameer Helps You Get Insights from Big Data Analytics Faster
At Datameer, we make big data analytics so simple that anyone can turn customer data into insights – and start seeing real benefits in just 2-4 weeks. There’s no need for a technical specialist or data scientist to model, integrate, cleanse, prepare, analyze and visualize your data because your business analysts can do this themselves. We provide a one-stop-solution for getting all of your Web, advertising, mobile, social media, transaction, marketing automation, CRM and other third-party data into Hadoop; analyzing that data; and visualizing your results using wizard-led data integration, point-and-click analytics, and drag-and-drop visualizations.
With over 55 out-of-the-box connectors to all major data sources and over 250 analytic functions – all available in a simple-to-use spreadsheet interface – Datameer empowers business analysts to easily aggregate and prepare all customer behavior data so they can:
- Rapidly combine and enrich existing data sets with third-party, customer, and other data
- Perform ad-hoc analytics to test what-if scenarios
- Better understand the customer journey and identify the best campaigns that yield conversion
- Identify the behaviors of customers at risk of churn so customer retention teams can intervene
With Datameer, you can perform customer path and market basket analysis and review decision trees to determine who and what led to the acquisition of certain products for each demographic. And you can perform interactive data discovery to identify the most common customer path and sequence of events that led to a purchase.Learn How