Evolving Web Metrics to Include Multichannel Analysis
Certainly business on the Internet has seen its share of change, and there is still potential for growth and opportunity ahead of us, but the tone is different.There is a renewed focus on business fundamentals such as profitability and return on investment. There is also the realization that the Web is just one of many channels through which your customers might interact.
This is not to say that the Internet isn't important, quite the contrary. The Internet has proven itself a valuable channel for interacting with customers - as an enabler for commerce, both business to business and business to consumer. It has allowed companies to magnify their presence and enlarge their reach while at the same time lowering the cost of servicing customers. It has been a prime channel for marketers - the perfect medium for moving quickly from trial and measure to good campaigns. Moreover, the Internet has provided us with rich data about customer behavior, attitudes, and transactions.
The Internet is just one of many channels through which you interact with your customers, but it is an important one for gathering information.
The Web analysis journey begins with basic reporting about Web traffic, usually hits and page views. It moves from defining a "visitor" to gathering information on the behavior of that visitor on the Web site. Concepts from traditional marketing analytics or financial metrics are borrowed and adapted to create a new breed of Web metrics, sometimes referred to as e- metrics. Metrics such as user recency, user frequency, visit trajectory, visit velocity, acquisition cost, conversion cost and content freshness factor all help express the relationship between customers, Web sites and the company's financial performance.
As a natural extension, these metrics have always been combined with data from other sources. While e-metrics focus on the online business, they can help the organization understand the customer in the context of the overall business. Data from user registration, product catalogs, dynamic content engines and e- commerce engines is correlated with the Web behavioral data. Bringing in this additional data helps to supplement online analysis, and for sophisticated companies summarized information from the Web can also be pushed into other systems for context about interactions with the Web channel. Metrics, segments, profiles or scores are exported for targeting online campaigns and personalization or for storing in the CRM application or data warehouses.
However, the emphasis of correlating Web data with other business data is shifting away from just providing context and moving toward providing an integrated view across all channels. This is driving the evolution of Web analytics projects into to multichannel and cross-channel analytics. The importance of integrating these other touchpoints is underscored as more and more customers are interacting with businesses through more than one touchpoint: by going into a retail location, calling up through the call center or using the Web and e-mail. New questions about customer interaction with different channels are being raised:
- How many sales purchases and service interactions occurred this week through each channel?
- What is the total revenue generated from each channel?
- What is the average cost per interaction per channel?
- Which channels do different customer segments user?
- How many customers utilize one, two, three and four or more channels?
- Which interactions with customers began but were not completed?
- Which interactions with customers are started in one channel and completed in another?
- What is the success/completion rate of interactions with customers in each channel?
At the same time, new business demands are being placed on companies and driving the need to integrate multiple channels.
New Business Demands
Reducing Cost through Better Channel Management. It is no secret that certain customer service channels cost companies more to maintain. For example, servicing a customer request through a call center typically costs multiple dollars; whereas, the same transaction can costs cents through the Web. Migrating customers from the more costly channels to the cheaper ones has been proven to save companies massive amounts of money.
Improving Retention and Loyalty. Companies also want to improve existing customer retention and loyalty. Increased customer retention typically comes from better servicing of customers, which is driven by superior communication (e.g., updates on insurance claim status) and ease of completing key transactions (e.g., submitting an insurance claim). In order to offer the best customer experience, companies integrate the different operational systems so that all departments can share the customer information.
Improving Acquisition. Companies want and need to do a better job of acquiring new customers. Improving acquisition improves top line revenue and increases company market share. Marketing, sales and e- commerce divisions do all they can to attract and convert more customers as cheaply as possible. Multichannel analytics typically improve the company bottom line by improving the messaging to prospects and streamlining online user interfaces for converting customers.
In turn, these new questions being asked and new business challenges placed on organizations will drive an evolution of e-metrics such as channel mix, channel costs, channel revenue and channel migration. How can your organization adapt its Web analytics projects to meet the challenges of this multichannel environment?
Web Analytics in a Multichannel Environment
Refine Customer Segments. Companies should improve their segmentation by combining demographic and firmographic information with the rich online behavioral information that Web behavior provides. Using these refined segments, companies personalize content, target key messages and improve online interfaces with the goals of first, increasing revenue through better customer retention and acquisition; and second, reducing costs through migration of customers between the channels.
Improve Marketing Communication/Campaign Effectiveness. Marketing and general customer communication campaign effectiveness are a function of the medium used to contact the targets, the message presented to the individuals and the market or segment being targeted. Web analytics can provide customers a unique perspective that includes behavioral information that has not previously been available in the offline channels. For example, imagine if the person putting together a customer communication knew that an existing customer had viewed some online material that indicated they were prime for a particular campaign.
Improve Call Center/Customer Interactions.Customers and prospects contact the call centers. The same individuals log into the Web sites to investigate products or serve themselves. Until recently, companies considered the online channel its own separate island of customer interactions and data. Unfortunately, this means that call service representatives in the call centers have not had any context about the customer's online behavior. For example, imagine if a customer service representative was able to see that a customer had tried to logon to a self-service interface but failed. That customer service representative would be able to work with the customer to educate them about how to find what they wanted or get past the hurdle that prevented a successful online experience..
This is a bold call to action. It potentially involves building a broad infrastructure for multichannel analytics, integrating Web data with sales force automation, call center, campaign management and financial data. Understanding the complexities of how different users interact with different channels is a daunting task. However, faster service, lower costs, higher customer satisfaction, improved retention, stronger loyalty - these are the promises of integrating multichannel analytics into your metric definitions.
For more information on related topics visit the following related portals...
Jay Henderson is a product marketing manager at the CustomerCentric Solutions division of SPSS, which focuses on helping businesses improve profitability in complex web and multichannel environments.
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