Customer 360 is the idea that companies can get a complete view of customers by aggregating data from the various touch points that a customer may use to contact a company to purchase products and receive service and support.
In today’s omnichannel Retail & E-commerce world, the number of touchpoints that connect retailers to their customers has multiplied drastically. Across ecommerce, in-store, social media, and mobile apps, customers are constantly shopping, liking, saving, and favouriting– all of which leaves a trail for retailers to utilize.
Retailers have always been in pursuit of customer 360, long before the digital technologies of today. So, a modern 360 customer view is about taking all the data and information in a customer profile and using the latest AI and analytics systems to improve customer service, personalized service, and overall retail operations.
The fundamental challenge is to collect the data and the next task is to make sense of the data by connecting the dots, or what we call data touchpoints. Customer 360 view helps in channelizing your target marketing more efficiently.
There are different types of customer data: Transactional Data, Demographic Data, Behavioural Data and Social Listening Data.
This data is usually considered as data around various categories and products that customers browse on websites, ecommerce, retail stores, or mobile apps. This also includes products added to the cart, products abandoned in the cart, and even details like clicks, scrolls, visit on specific landing pages and the time spent there, etc. all form part of such data. It helps identify key points in a customer journey (where customers get stuck/leave/convert).
Customer demographics is statistical data relating to the target population and particular groups within it. This data can include such as gender, age, marital status and education, location, purchase intent, lifestyle information, buyer type and more. This data is vital for customer segmentation and defining target segments.
This is the data collected through social media engagement with customers. Analysis of likes and comments on posts, customers’ online reviews or social media posts about a product/service helps identify customer preferences, reveal customer complaints and problems to solve and recognize customer attitude to products/services in particular and company brand in general.
It includes analysis of data such as product/service purchases, returns, reservations, etc. It gives insights into customers’ spending habits, payment method preference, the share of wallet, etc.
Customer 360 provides deep understanding of customers and helps to create micro target segments for personalized campaigns. Analysis of customer data helps in identifying customers that are most likely to churn, key factors that influence customer decisions, key churn drivers, etc. for developing highly customized customer acquisition/retention strategies. Also, specific customer segments, we get insights to run cross-sell and upsell campaigns, retargeting campaigns etc.
By creating micro segments and analysing customer data on every customer touch-point, you can gain valuable insights about how your customers interact with your brand. Customer insights can also be in the form of anticipated future behaviour such as churn prediction. This can make a business be well prepared for future opportunities. Businesses looking to establish a new product can use 360-degree customer view to make decisions and predict the future.
The 360-degree customer view contributes greatly to customer loyalty and retention. Through having unique insights to having personalized approaches, customers develop a connection and relation to the brand/business. Personalized campaigns based on behaviour analytics significantly increases customer satisfaction.
Collecting customer data throughout the customer journey and creating micro-segments helps to easily track the most relevant KPIs (conversion rate, CLTV, CSAT, churn rate, loyalty rate, net promoter score, etc.), visualize customer interactions across various touchpoints, collaborate and share key analytics findings with colleagues.
By implementing an AI-driven model like the one we’ve described above, industries can monitor the customer experience in real time and generate insights which would allow service providers to provide a seamless customer experience and intervene in a timely manner for effective service recovery.
TransOrg can create a customer 360° view which will enable a complete and accurate picture of every customer by aggregating all each customer’s structured and unstructured data from across the business touch points.
Artificial Intelligence | Nov 30, 2018»
Artificial Intelligence | Nov 30, 2018»
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