By evolving from web analytics to online customer analytics organizations have the chance to achieve true customer relevance explains Malcolm Duckett, VP Marketing & Operations, Speed-Trap.
In a world of customer power and unlimited consumer choice, marketing is being forced to change its emphasis in order to build closer relationships and greater customer loyalty. And key to this is achieving customer relevance which demands the in depth understanding of customers initially promised by the rich source of online data. Unfortunately, most organizations are still fundamentally constrained by the irrelevant and patently inaccurate information delivered by web analytics for the past decade.
By evolving from web analytics to online customer analytics organizations have the chance to achieve true customer relevance. With this business focused analysis of online channel data, and a detailed view of customer’s interactions with, and experience of the business, an organization can start to drive effective personalization, marketing, BI, CRM, pricing optimization and anti-fraud applications across the enterprise,
Customer Understanding
While the development of CRM systems signalled a transition to customer orientation in businesses, these early systems tended to try to put the focus on the ‘M’ in CRM, aiming to help businesses better manage their customers. With the emergence of customer power through the social networking revolution and comparison sites, there are few businesses today that still believe they are in a position to manage customers.
Instead the goal now is to be relevant to customers; a focus that leads to the modern marketing mantra of ‘right message, right customer, right time’. But while it might appear obvious, a business can only be relevant to the customer if an organization has in depth understanding. It must understand each customer as an individual, with objectives, interests, preferences, likes and dislikes… and note that an individual’s needs change over time, and their opinion of the business (when considered en masse) will make or break the company!
The CRM systems required today are far more focused on the ‘C’ aspects of the acronym and the ‘relationship’ part might be better cast as ‘relevance’…
Harnessing Information
If Customer Relevance Management systems are to deliver the required customer insight they require one key component: reliable, accurate and detailed data on customers. This focus on the customer needs to embrace the idea that customers are individuals, and organize data in ‘customer structures’, and record ‘customer events’. Organizations must enable the marketing and business functions to use business intelligence (BI) systems to extract the insight and understanding to allow the business to identify how to be relevant and when they should say what to whom!
And key to achieving this understanding is harnessing the richest source of information available to the business: the online channel. Traditionally marketing programs have had to work with very limited sales data from sources like loyalty or reward cards and back office systems. And while remarkable successes such as Tesco and Amex have emerged from using this data, the online channel is so much more data rich.
Moreover, historically, much of the data available – such as web analytics data – was not attributable to individuals. Indeed, despite the huge interest in this area, web analytics has consistently failed to provide a clear ROI for two key reasons: it focuses on web data when the business is focused on business data; and it has failed to deliver data of sufficient quality and reliability to be included in the data warehouse.
Hence it is almost impossible for a marketing program to ‘action’ such data – you don’t know who to aim at when pulling the campaign trigger!
Business Data
In the online environment an organization does not only learn about an individual’s product purchases, but also about intent (what they searched for); about aspiration (the products they looked at); about demographics (where they are, who they work for); about ‘history’ (from the very first time they visited your site); about acquisition (where they came from); about experience (how the site worked for them); about current activity’ (what they are doing right now); and much more.
This channel is often a potential customer’s first point of contact with an organization. Therefore understanding how they have interacted with applications and web sites is key when communicating and converting an individual from ‘browser’ to ‘customer’.
Gathering data from the online channel has traditionally been seen as a complex, technical task, often involving armies of developers to code ‘business logic’ into web pages via ‘tags’. This approach has proven very costly (and error prone) to implement with long deployment cycles leading to marginal business benefits.
The latest generation of solutions overcome these issues by automating the capture and allowing the business to extract the ‘meaning’ from a customer’s journey and thereby open the door to major improvements in efficiency, profitability and growth.
Data Capture
The latest generation of data capture technologies (OCDC systems) have moved the capture function from the web server to the client device, providing data about customer interactions (actions, responses, behavior, environment), rather than data about web-server events (like hits, clicks, page impressions etc.).
Furthermore, the analysis of this data and the storage of the resulting information is structured by ‘customer’ – real, live individuals (even if they remain anonymous), as opposed to the traditional page oriented analysis or construction of rather shaky analogs of people (like ‘Unique Visitors’). Finally, by utilizing the latest AJAX, and document-object-model (DOM) and event-driven technologies the data accuracy and contextualization is on a par with the best offline ETL and data capture processes.
Simple yet Effective
There is no need to become incredibly complex about customer understanding and in depth analytics: really simple personalization projects can deliver significant benefits. Dutch insurance company FBTO segmented visitors into one of four groups based on their previous activity. Combining this segmentation with an understanding of which of the four product groups they appeared to be interested in, the company personalized a single landing page image.
As a result, FBTO increased conversion rates by 15%. By using the same data to personalize call centre interactions the business delivered another campaign which resulted in a sale to every third person called. That is relevant!
By Malcolm Duckett
VP Marketing & Operations
Speed-Trap
www.speed-trap.com