How Behavioral Analytics Fuels More Personalized Marketing

Thought Leadership White PaperIBM Software Enterprise Marketing Management

Oh behave! How behavioral analytics fuels more personalized marketing

2 Oh behave! How behavioral analytics fuels more personalized marketing

Behavioral web analytics: A gold mine for increasing marketing valueBehavioral web analytics isn’t mere theory: many companies are already applying it to improve their web marketing performance and profitability. Amazon, who has long leveraged web behavioral data to make product recommendations, is one of the best-known examples, but many other firms are also effectively leveraging behavioral web data to personalize interactions.

• A leading online marketplace provides personalized suggestions of available items that appeal to traders’ interests based on their recent searches, bids, and purchases. This feature has led to substantial increases in click-through rates.

• A leading online bank uses advanced behavioral web analytics to identify customers that abandon an application process and then deliver a multi wave campaign that recaptures and converts a significant number of leads. The strategy leverages event triggers that start a communication stream when the online application is abandoned. It draws upon email, direct mail, and even calls from relationship managers. The program has not only boosted conversion rates, but by eliminating communication overlap and reducing contact fatigue, it has also enhanced customer loyalty.

• A leading auto manufacturer has improved the way it prioritizes leads that originate on its websites. To prioritize leads more effectively, the auto manufacturer profiles each prospect’s interests based on site behavior and scores the prospect’s propensity for making a purchase. Leads marked as “hot” are twice as likely to close as “average” leads, and six times likelier to close than “colder” leads. Using this data, dealers can now focus on their best opportunities to drive sales needed most.

If you are like most marketers, you are facing an enormous headwind: you need to increase marketing returns at a time when conventional marketing techniques are increasingly ineffective and real-time dialogue is becoming a norm.

To improve returns, many marketers are focusing on optimizing their websites and social media properties to make them more dynamic and relevant to their audience. Doing that requires creating dynamic content that supports the interests and preferences of their various visitor segments. For maximum impact and return, marketers must go beyond segment marketing and click reporting and create a personal dialogue with each visitor. Behavioral web analytics can fuel this personalization process by providing specific insights about each segment and individual. Uncover the gold mine that lies within behavioral data, identify the specific nuggets to mine, and learn how to leverage behavior data to increase marketing returns at every stage of the customer life cycle, both online and offline.

Two uses of web analytics: Aggregate and individual-level insightsConventionally, web marketers use analytics at an aggregate level, reporting on the performance of their websites and online advertising, so they can adjust their efforts to improve the results. Analytics are a worthwhile application that can deliver excellent return on investment (ROI).

However, if marketers do not also leverage web analytics as arch source of behavioral insights on visitor segments and individual prospects and customers, they are squandering a huge opportunity to improve marketing ROI. Web analytics can play a far more direct role in engaging customers, improving customer experiences, and increasing sales, by enabling companies to deeply personalize their communications and interactions.

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These insights can be transformed into targeted marketing initiatives at every stage of the customer life cycle (see Figure 2).

Figure 2: Mapping life cycle stages and business goals to initiatives that can be driven by behavioral analysis

The Typical customer and visitor-level behavioral web analytics triggers table on page 4 lists typical website session events to watch for in various industries.

Figure 1: A web analytics funnel report helps identify individuals you can target with relevant marketing offers.

Identifying what nuggets to mineBehavioral analysis can reveal actionable insights into segments, individual prospects, and customers. For example:

• Individual personal preferences and current product or content interests

• Where individuals stand within the buying cycle or customer life cycle

• When they are most susceptible to being persuaded, converted, or up-sold

• When timely action must be taken to retain them• Which offers are most relevant and persuasive• How much each individual is willing to spend


For example, a fashion retailer can use behavioral web analytics to profile customers based on the price categories and clothing styles they are browsing. Marketers can then use these insights to personalize emails with items that match these price levels and styles. Similarly, you can leverage these insights in other

outbound communications or across inbound channels. For example, when a customer phones the call center to inquire about a shipment, the company’s IVR or CRM systems could suggest promotions that fit the same profile.

Typical customer and visitor-level behavioral web analytics triggers (by industry)

Retail Finance Telco Publishing B2B

Onsite behavioral targeting Product categories or features studied, example: clothes colors, styles, and price levels selected on a fashion retailer’s site

Products and educational content studied, example: IRA calculators

Service details studied, example: regional coverage maps

Content categories preferred, example: type of sports

Products and educational content studied, example: web pages covering technical details versus business benefits

Remarketing Contents of abandoned shopping carts

Abandoned online forms for quotes or opening accounts

Cross-sell offers received by email or on the site, yet not clicked

Subscription options studied but not purchased

When online lead form is abandoned, capture company name through IP address, and target by mail, phone sales, or both

On-boarding Bad review rating given after completed product purchase; or failed site searches for accessories performed

Missing or failed events, example: no or unsuccessful online registration, or failed site searches

Same as Finance. Also, missing click-throughs from marketing emails

After registration, visitors don’t return to site, or read few content categories

Unsuccessful searches in the self-help knowledge base or keywords used that indicate issues with using the purchased product

Cross- and up-sell Products viewed frequently together

Account options studied but not yet owned

Available service features studied on the site, example: email access

Articles read in a category that the reader doesn’t normally use

Products studied that customer does not yet own

Retention marketing Fewer product categories viewed, less frequent visits, or both

Repeated reviews of loan payoff amounts

Review of contract duration period, or click-throughs from sites that compare competitors

Fewer content categories read, and/or less frequent visits

Reduced frequency of self-service logins to the customer support area, or searches performed in knowledge base with no results found

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Figure 3: Registered customers and their product and spending preferences as exhibited on the website

Five steps to Personalized Marketing success with behavioral analyticsMany organizations, however, struggle to capture, organize, and effectively leverage behavioral web data to drive marketing programs. IBM has outlined a five-step path to help marketers progressively mature their capabilities and expand the use of web analytics from aggregate-level reporting to leveraging behavioral insights to fuel Personalized Marketing.

Figure 4: Five steps to behavioral analytics

Stage 1: Site analysis (Reporting)At most organizations, web analytics begins as a site analysis solution, intended to monitor site health, report on-site activity, and prove ROI for the online channel. In this step, web analytics answers basic questions such as:

• How many visitors are coming to my site?• How are visitors using it?• How are visitors finding it?


Stage 2: Site and advertising optimizationTo begin generating substantial business value, web analytics must evolve at least to Stage 2: site and advertising optimization. In this stage, web analysts seek to identify bottlenecks; for example, web pages that aren’t performing well. Marketers experiment to identify and assess opportunities for overcoming these bottlenecks and increase returns. Marketers are asking:

• How can I improve our website’s structure and content to increase conversion rates?

• How can I reallocate online advertising spend to attract more profitable customers?

Stage 3: Segment targetingIn Stage 3, marketers realize that there is no such thing as an “optimized page.” That’s because different groups of visitors come to the same page with different goals in mind. Therefore, in Stage 3, marketers use behavioral analysis to define their most valuable customer segments and identify the dynamic content that’s most effective with each segment. For anonymous website visitors, this content may be delivered on the site through behavioral targeting. Registered online visitors can also be targeted via personalized email or SMS. Questions that can be answered include:

• What are the most valuable visitor segments for my business, grouped by common click behavior along with other information I possess about them?

• What content or promotional offers are best suited for targeting each segment on the site?

• How can I begin leveraging what I learn on my site to improve my other communications?

Stage 4: Personalized Marketing (Online only)While marketers who move to Stage 3 are laying crucial ground-work for personalized, customer-centric marketing, they typically find ROI temporarily flattening out. There are limits to the amount of value generated through segmentation. Reigniting improvements in business value requires innovation — and personalization.

In Stage 4, marketers refine targeting beyond the group level to the individual visitor level. Marketers use individualized behavioral analysis to fuel Personalized Marketing; such as, to build a dialogue based on each visitor’s past and current behavior. To achieve this goal, marketers ask and answer questions such as:

• What is the most effective website, email, or SMS content for each individual based on prior site behavior?

• Should I reach out online to an individual customer right now with messages aimed at onboarding, cross-selling, or retention?

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Figure 5: Using behavioral insights from web analytics to drive Personalized Marketing across offline and online channels

Stage 5: Personalized Marketing (Cross-channel)Finally, in Stage 5, marketers extend the Personalized Marketing dialogue with identified cross-channel customers to include offline as well as online channels. Supported by behavioral web analytics, offline communications — for example, promotional offers delivered through a call center IVR system — build on all past and current customer behavior. In addition, insights from offline customer transactions are used in determining the web or email content deemed most relevant to each customer.

Whether interactions are outbound or inbound, behavioral analysis can answer questions like:

• What is the best way for me to continue my ongoing sales dialogue with this individual?

• Based on what I know about this individual’s prior interactions and transactions across all channels, what is the best offer or communication I can make next?

• When do I make that offer?


Climb the five-step growth pathSo how do you move up the behavioral analytics maturity model, rapidly and cost-effectively? The table on page 9 defines the specific organizational know-how and technology requirements you’ll need at each stage.

Make the most of the marketing team you already haveMany marketing organizations have virtually all the skills they need to begin applying behavioral web analytics to their marketing efforts. However, these capabilities are often spread across the enterprise in disconnected teams; for example, separate teams for online versus relationship marketing. To succeed, marketing organizations must make it possible for these siloed resources to work together. They must also overcome some widely held misconceptions about web analytics.

For example, some relationship marketers still hold beliefs about web analytics that might have been accurate years ago, but no longer are:

“Web analytics is summary-level data; it isn’t useful for behavioral data.” Today’s best web analytics solutions — notably the IBM Enterprise Marketing Management (EMM) Suite — provides behavioral profile data at the visitor/customer level in a readily accessible web data mart.

“Click data is too much of a ‘fire hose’: you can’t make sense of every click.” Successful marketers have learned how to focus their attention on a subset of key online events that are most likely to drive actions important to their business. These events include purchase intent, abandoned shopping carts, and clicks that drive content sharing.

“Web analytics is only interesting to the web team, not my team.” Marketers that ignore behavioral web data are disregarding an indispensable resource.

Online marketers also have their misconceptions:

“Marketing is primarily about ‘acquire, convert, retain.’” These misconceptions miss the urgent importance of growing each customer’s Lifetime Value (LTV) — a concept that is incompletely expressed by “retention,” and can only be achieved through a more customer-centric approach.

“I couldn’t possibly look at each individual visitor.” It can’t be done manually. But your company’s relationship marketers can take advantage of technology that can automate analysis and action at the level of individual customers.

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Typical behavioral analysis based marketing triggers (by industry)

Stage 1 Stage 2 Stage 3 Stage 4 Stage 5

Requirements Site analysis (Reporting)

Site & ad optimization Segment targeting Personalized Marketing online only

Personalized Marketing online + offline

Organizational maturity Define site and marketing goals clearly, so they can be translated into web analytics Key Performance Indicators (KPIs)

Set improvement goals, and manage toward them; prioritize testing above subjective opinions

Identify key segments relevant to the business, and see the company/website through the eyes of representatives from each segments

Commit to personalization and relevancy as your paradigm of doing business online (versus ”spamming”)

Commit to a customer-centric business strategy that encompasses and integrates all channels

Know-how and skills Measure what matters, instead of attempting to measure everything

Design and run tests, understand their statistical significance, and act on the results by adjusting websites or ad spend allocation accordingly

Discover meaningful behavioral segments from click data and visitor registration information using web analytics and data mining techniques

Link site visitors to their registered customer information and identify the life cycle events that are actionable for marketing

Link the identity of customers across online and offline channels and identify the life cycle of actionable events for marketing

Technology for customer awareness

Self-service access to personalized metrics for each role in the organization

A/B analytics for website and online advertisements

Segmentation analytics (Example: web analytics and data mining solutions) for both click data and registered customer data

Web data mart that provides open, secure access to granular data on each individual’s website interaction history

Web data mart for online interactions, as well as access to offline history of transactions, campaigns, and responses

Behavioral targeting/decisioning technology

N/A Assign visitors randomly to test groups

Define business rules for targeting segments, and use self-learning mechanisms to refine targeting

Select the most effective content for each individual online customer in real time, reflecting past and current click data, customer insights, and business rules

Choose the most effective marketing communication or of fer for each customer, reflecting past and current interactions both online and offline

Technology for delivering targeted content

N/A A/B test automation for site & advertisements

Deliver targeted content to each segment via site advertisements, recommended content or products, email, SMS, or other means

Deliver targeted content to each individual via personalized site content, email, SMS, or other means

Cater targeted content to each individual, regardless of the inbound or outbound channel each interaction occurs in


IBM can help you take the next stepOur EMM suite helps companies drive business value by optimizing their marketing relevancy for each segment and individual customer or prospect. Our leading Personalized Marketing solutions give marketing organizations the capability to capture web behavioral data and then identify and act on insights to engage customers in a relevant dialogue. IBM knows what works and how to overcome the obstacles. If you are ready to trans-form web analytics from a mere aggregate-level reporting tool into a powerful enabler of behavioral analysis and targeting, it’s time to learn more about what IBM solutions can do to improve your marketing ROI.

About IBM Enterprise Marketing Management The IBM Enterprise Marketing Management (EMM) Suite is an end-to-end, integrated set of capabilities designed exclusively for the needs of marketing and related organizations. Integrating and streamlining all aspects of marketing, IBM’s EMM Suite empowers organizations and individuals to turn their passion for marketing into valuable customer relationships and more profitable, efficient, timely, and measurable business outcomes.

Delivered on premises or in the Cloud, the IBM EMM Suite of software solutions gives marketers the tools and insight they need to create individual customer value at every touch. The IBM EMM Suite helps marketers to understand customer wants and needs and leverage that understanding to engage buyers in highly relevant, interactive dialogs across digital, social, and traditional marketing channels.

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Designed to address the specific needs of particular marketing and merchandising users, the IBM EMM Suite is comprised of five individual solutions. Digital Marketing Optimization enables digital marketers to orchestrate relevant digital interactions to attract and retain new visitors and grow revenue throughout the customer’s lifecycle. With Customer Experience Optimization eCommerce professionals can turn visitors into repeat customers and loyal advocates by improving the digital experience of every customer. With Cross-Channel Marketing Optimization customer relationship marketers can engage customers in a one-to-one dialogue across channels to grow revenue throughout the customer’s lifecycle. Price, Promotion and Product Mix Optimization allows merchandisers and sales planners to make price, promotion and product mix decisions that maximize profit and inventory utilization. And with Marketing Performance Optimization, marketing leaders, planners and decision-makers can model and assess mix, and manage marketing operations to maximize ROI.

Over 2,500 organizations around the world use IBM EMM solutions to help manage the pressures of increasing marketing complexity while delivering improved revenue and measurable results. IBM’s time-tested and comprehensive offerings are giving companies such as Dannon, E*TRADE, ING, Orvis, PETCO, Telefonica | Vivo, United Airlines and wehkamp.nl the power and flexibility required to provide their customers and prospects with what they expect today — a more consistent and relevant experience across all channels.

For more informationTo learn more about IBM’s web analytics offerings, please contact your IBM marketing representative or IBM Business Partner, or visit the following website: ibm.com/software/marketing-solutions

http://www.ibm.com/software/marketing-solutions

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How Behavioral Analytics Fuels More Personalized Marketing

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