Customer Analytics Overview: A true 360-degree view of a customer can’t be sourced exclusively from internal data let alone from a single system or department. Organizations trying to correlate customer interactions, transaction history, and behaviors to improve customer acquisition ROI and retention struggle to aggregate and analyze data and signals across operational, social engagement, customer experience, and outreach systems to provide real-time customer insights.
Why Customer Analytics?
Customer Analytics helps enterprise-wide stakeholders bridge the gap between customer and sales and marketing, whether the goals are to increase revenue, build customer loyalty, and create a memorable brand experience. While it’s possible to define customer journey from a single source, many organizations have a fragmented view of the customer journey that spans disparate systems and organizational silos. Without a unified view, you won’t be able to determine how customers are interacting with your brand in order to improve customer retention and better market to them. Data can’t speak if you aren’t listening. To understand a customer’s journey, you need to assess the different touch points customers experience while engaging with a brand.
Customer Analytics Architecture
Customer Analytics are an important component of customer experience management that measure both transactional and emotional customer journeys. Think of a 360-degree view of a customer in this context and you get the idea: any way you interact with a customer can be tracked and measured. The analytics architecture is the underpinning for how to help siloed systems communicate and reconcile their various information and knowledge sets so the business can act on the information.
It’s critical that the tools and process involved with creating customer analytics have the ability to integrate and orchestrate the disparate data systems and applications. This needs to include legacy and third-party applications in order to get the best view of customer behaviors and actions and, ultimately, drive change throughout the entire company.
By going beyond manual reports and spreadsheets, organizations can dive deeper into customer intelligence and journey mapping, companies can identify the right products, services, and content, build trusted relationships, and optimize customer engagement to generate greater revenue and customer satisfaction.
How to Measure a Customer’s Journey from One Point to Another
The journey from lead to customer can vary drastically depending on the channel, the stage of the sales process, and other factors. You need to know the core metrics and activities that you need to track in order to strengthen revenue streams. Unfortunately, these are often locked in multiple systems and lack a holistic view of business heath. This is where a cloud data warehouse can aggregate multiple sources providing a holistic, unified view of business health. A cloud data warehouse can also provide the ability to integrate, cleanse and ensure data is accurate across systems. Once you have access to all the data, you can begin mapping your customer journey. This will help to better measure the alignment of the customer experience with their overall business objectives and identify customer problems and challenges along the path to purchase.
While solutions like CRM, marketing automation and even customer data platforms are useful in collecting and managing customer data, they still often fall short when bring together internal or historical system data. Creating a holistic view of a customer’s journey, which then provides the customer with a truly 360-degree view of the brand, requires an end-to-end view of the customer’s data. Customer Analytics is the answer to the hunger for a holistic view of the customer. By integrating customer data from across systems, tools, departments and regions, enterprises can achieve real-time data and deeper customer insights to increase the value of each customer, lead, and customer experience.