Introducing IBM Digital Analytics Lifecycle

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Introducing IBM Digital

Analytics Lifecycle

Perfecting the science of the customer journey

Introduction IBM® Digital Analytics Lifecycle is the industry’s first application geared to enable online marketers to track and understand how customers progress through long-term purchasing and conversion lifecycles. A customer conversion lifecycle is characterized by milestones ranging from first-time visitors to valued customers who engage with your brand through repeat purchases, newsletter

subscriptions, product reviews and social media channels like Facebook and Twitter.

Using IBM Digital Analytics Lifetime Individual Visitor Experience (LIVE) Profiles data, IBM Digital Analytics Lifecycle gives online marketers a broad perspective into the customer conversion lifecycle, enabling you to evaluate which marketing campaigns are most effective in prompting customers to progress from one milestone to the next. IBM Digital Analytics Lifecycle also supports a range of non-purchasing lifecycles by value, frequency, downloads and lead-generation, making it applicable across a range of industries. Seamless integration with IBM marketing solutions enables you to convert insights into action by targeting customers with personalized email, display ads, on-site recommendations and more.

Why IBM Digital Analytics Lifecycle?

Traditionally, many online marketers have based web analytics largely on single-session clickstream data, tying conversion to the customer’s last marketing touchpoint. For example, a web analytics solution would show that a customer clicked on a pro-motion in an email newsletter to land at a home page and moved through pages for electronics, TVs, furniture and couches before exiting. If the customer bought a TV, the email newsletter would receive credit for the sale without consider-ation for the customer’s engagement with other online channels or touchpoints.

The issue is that most conversions occur only after multiple days and numerous website visits or other online interactions. In fact, analysis of IBM Digital Analytics Benchmark data aggregated from multiple retailers has shown that customers engage with your brand an average of 5.5 times before conver-sion. Over-reliance on basic web analytics can prevent market-ers from fully undmarket-erstanding the customer’s journey, the buying lifecycle and key points of influence over a period of many months.

Example Purchasing Lifecycle Example Event Lifecycle

14.8 Days 2.2 Sessions 7.9 Days 1.4 Sessions 63.1 Days 7.5 Sessions 19.9 Days 1.2 Sessions 78.9 Days 5.2 Sessions User Review Writer 2x Buyer 3x Buyer Newsletter Subscriber 14.8 Days 2.2 Sessions 7.9 Days 1.4 Sessions 63.1 Days 7.5 Sessions 19.9 Days 1.2 Sessions 78.9 Days 5.2 Sessions Forum Contributor Facebook Fan 2x Downloader Subscriber Shopper 1x Buyer New Visitor Whitepaper Downloader

Figure 1: Typical purchasing and event lifecycle progressions.

The need for online marketers to analyze customers and not just visits is driven by the increasing complexity of web interac-tions, widespread demand among sophisticated customers for greater personalization and fierce competition for customer attention. Marketers need to better understand how customers use and are influenced by various campaigns and channels over-extended time periods.

Popular channels and campaigns that influence customers are: • Paid and natural search

• Email communications • Display advertising • On-site recommendations

• Social media channels like Facebook and Twitter • On-site communities and customer reviews

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Understanding the customer conversion

lifecycle

As a next step in the evolution of web analytics and online marketing, IBM Digital Analytics Lifecycle gives marketers an innovative approach to analyzing long-term customer activity data.

IBM Digital Analytics Lifecycle features built-in snapshots and the ability to customize conversion lifecycle views and drill down to underlying data. In Figure 2, the Lifecycle interface reflects a monthly snapshot of activity from the perspective of lifecycle milestones.

The interface shows a total of 1,293,042 unique visitors and the raw numbers and percentages of individuals who became shoppers, 1x buyers, 2x buyers and 3x–5x buyers in that population. It also shows the average number of days and sessions it took to progress to those milestones. The interface also illustrates “migrators,” or sets of individuals who have progressed from one milestone to the next, and the time and sessions on average between each progression.

IBM Digital Analytics Lifecycle enables you to view and compare such data sets over any range of timeframes, such as Q1 versus Q2, orQ4 versus Q4 year over year, and by a number of predefined and customizable milestones and data attributes. For example, the view could reflect products purchased, average order value, social media activity, product review contributions and any segment of the population by milestone.

For instance, in Figure 3, IBM Digital Analytics Lifecycle shows the top products purchased by 2x buyers. Such data can provide marketers with invaluable insights helping customize cross sell and up sell campaigns to 1x buyers, prompting them to quickly progress to the 2x buyer milestone and beyond.

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While this example looks at a purchasing lifecycle, IBM Digital Analytics Lifecycle supports other types of lifecycles relevant to companies in a variety of industries, such as financial services, higher education, consumer and enterprise software sales, travel and hospitality, media and entertainment, and

telecommunications.

Examples of other customer lifecycle milestones include: • Lead Generation Lifecycle

–Stage 1 prospect → stage 2 prospect → stage 3 prospect • Frequency Lifecycle

–1 session visitor → 2 session visitor → 3-5 session visitor → 6-10 session visitor → 10+ session visitor

• Event Lifecycle

–Non-event initiator→event initiator→1x event

completer→2x event completer→3-5x event completer → 6x event completer

• Value Lifecycle

–$0 value visitors→$100 value visitors → $500 value visitors → $1000 value visitors → $5000 value visitors → $10,000 value visitors

• Downloader Lifecycle

–1 white paper downloader→2 white paper downloader→3 white paper downloader

• Student Lifecycle

–Browser→inquirer→downloader→Facebook fan→applicant → enrollee

Pinpointing key factors in lifecycle

progression

The real value lies in understanding what prompts customers to progress through the lifecycle, from one milestone to the next. Taking it a step further, online marketers should endeavor to understand what prompts certain segments of customers on their lifecycle journey.

Using IBM Digital Analytics Lifecycle data, your marketers can continuously optimize their initiatives to generate optimal value based on the insights into which campaigns, channels,

touchpoints and customer characteristics are in play. You can measure the time and sessions required for customers to progress through milestones. The solution also helps online marketers set goals to reduce the time it takes to reach milestones by using the marketing techniques that are most effective. You can explore which techniques and offers work best for early-stage customers and what is most effective for late-stage customers.

In Figure 4, IBM Digital Analytics Lifecycle illustrates top marketing influences on sets of individuals at different stages in the customer conversion lifecycle. For instance, paid search was most effective in driving migration from non-shopper to shopper, while email was most effective in prompting 2x buyers to become 3x buyers. Drill-down capabilities enable you to examine this data at a granular level.

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IBM Digital Analytics Lifecycle makes it easy for you to customize reports based on metrics you select, in addition to using its set of prebuilt metrics such as:

• Visitor population: Number of unique visitors who visited your website at least once in a given timeframe and met the segment criteria

• Average days to reach: Average number of days from start of a lifecycle period to reaching a milestone

• Average days in between: Average number of days for customers to progress from one milestone to the next • Average sessions to reach: Average number of sessions

from start of a lifecycle period to reaching a milestone • Average sessions in between: Average number of sessions

for customers to progress from one milestone to the next

Using insights to fuel marketing

applications

Use the insights you derive from IBM Digital Analytics Lifecycle to fuel your IBM marketing applications like email, display advertising and on-site recommendations. Since you are tracking customers as they migrate through lifecycle phases overtime, IBM Digital Analytics Lifecycle is uniquely suited for targeting of individuals who fall below the averages for time and number of sessions to progress to the next milestone.

Using your IBM Digital Analytics LIVE Profiles data, IBM Digital Analytics Lifecycle enables you to engage prospects and customers with personalized marketing based on where they are in the customer lifecycle, as well as the channels, campaigns, products and services they find most appealing. IBM Digital Analytics Lifecycle seamlessly integrates with the IBM LIVEmail personalized email solution, the IBM AdTarget display ad solution and the IBM Product Recommendations engine.

In Figure 5, a pop-up box in IBM Digital Analytics Lifecycle enables a user to select from a set of customer segments to

Conclusion

As consumers become more sophisticated and conversion cycles lengthen, it is imperative to know all the marketing touchpoints on the path to conversion. Understanding the time to reach each milestone lets online marketers know how quickly customers become more valuable. Understanding which marketing programs are most influential in prompting

customers to the next milestone helps marketers optimize their marketing mix and engagement strategies. IBM Digital Analytics Lifecycle is designed to give marketers the insight to optimize the customer lifecycle and improve migration between milestones.

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

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Please Recycle engage buyers in highly relevant, interactive dialogs across

digital, social, and traditional marketing channels.

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.

Introducing IBM Digital Analytics Lifecycle