Top performing organizations, including not only large enterprises but also a growing number of midsize and smaller companies, are steadily improving their cross-channel marketing capabilities, with a measurable impact on both cost reduction and revenue growth.
This Deep Dive analyst report explores how Top Performers are achieving success by deploying the right enabling technologies and analytic capabilities as well as by implementing the right performance metrics to track and measure campaign results within and across channels.
Specifically, it focuses on how companies of all sizes can generate and act upon customer intelligence using cloud-based multi-channel campaign management platforms that integrate features and capabilities that only a few years ago would have been found only in channel-specific solutions or large (and expensive) enterprise marketing suites.
Gleanster uses 2-3 key perfor- mance indicators (KPIs) to distinguish “Top Performers” from all other companies (“Everyone Else”) within a given data set, thereby establish- ing a basis for benchmarking best practices. By definition, Top Perform- ers are comprised of the top quartile of qualified survey respondents (QSRs).
The KPIs used for distinguishing Top Performers focus on performance metrics that speak to year-over-year improvement in relevant, measur- able areas. Not all KPIs are weighted equally. The KPIs used for this
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“Integrated multi- channel platforms generally combine the benefits of multiple best-of- breed components. These components include not only channel-specific technologies, but also self-service business intelligence and data visualization tools for “data discovery” and performance reporting. The platforms provide a single sign-on and the components are designed to work together seamlessly.”
Isabel Briggs Myers noted that the characteristic strengths in the ways that different people process information can vary dramatically. Some people are verbal processors. Others are visual processors. Some people respond more strongly to images, others to text. The most effective way to learn, they reasoned, was to map the different learning styles to each individual’s characteristic strengths. Moreover, they posited that the different styles when used in combination could become reinforcing components of the overall learning experience.
By the same token, different consumers have different channel preferences. Some prefer receiving brand-related messages via the mobile channel, for example, while others prefer email or direct mail. Some consumers like to interact with companies via the call center while others choose to engage primarily through social media. At the same time, when used in combination, the different channels can become reinforcing components of the overall customer experience.
The key to effective multi-channel campaign execution is collaboration. Campaigns should “collaborate” among channels — scanning a QR code in a print ad to receive information through video and text, for example, or typing in a URL promoted through a direct mail piece. The channels should be complementary. Each channel’s unique strengths should work toward the common goal of attracting, retaining and increasing the value of profitable customers. Ultimately, this goal should translate into higher returns on marketing investment, defined as increased marketing effectiveness for the same amount of marketing spend.
The ability to centrally manage the design, execution and measurement of marketing campaigns across a multitude of both offline and online channels is a big selling point when it comes to multi-channel campaign management platforms. According to Gleanster research, almost half (47%) of companies continue to rely on channel-specific technologies to manage campaigns that straddle two or more channels, as illustrated in Figure 1. At the same time, Top Performers are more than twice as likely as Everyone Else (69% compared to 34%) to leverage a single technology to support their multi-channel campaign manage- ment activities. Almost half (49%) of all organizations that don’t currently use an integrated solution state that they plan to adopt one within the next 12 months.
Integrated multi-channel platforms generally combine the benefits of multiple best-of-breed components. These components include not only channel-specific technologies, but also self-service business intelligence and data visualization tools for “data discovery” and performance reporting. The platforms provide a single sign-on and the components are designed to work together seamlessly.
The fact that the platforms are cloud- based is important, too, given that the pace of innovation and the diversity of functionality is evolving so rapidly in several online channels. On-premise software requires manual updating and is also generally difficult to customize, which means that organizations are often forced to adapt their processes to the package’s one-size-fits-all frameworks. Other obvious benefits include web-based access to data, wherever authorized individuals have Internet access, via desktops, tablets, or smartphones, and world-class infra- structure and security without hardware or software to maintain. The reduced investment in IT staff, hardware, and software matters, especially to smaller companies in an age when capital budgets have been static or shrinking.
To be fair, many marketing platforms are now largely cloud-based. The real differentiator, then, is the integrated nature of the platform. Compare the implementation of a multi-channel campaign management platform to the need to deploy each of the individual components — an email marketing solution, a mobile marketing solution, a social media marketing solution, an outbound call center solution, etc. on a standalone basis. Each solution has a different user interface. Each solution requires separate training and comes with separate support. Assessing and securing channel-specific campaign management and reporting capabilities from different solution providers can be a cumbersome process. Trying to cobble together a mix of incompat- ible marketing solutions, if only for the purpose of cohesive campaign reporting, can be an exercise in futility.
“Invariably, customer intelligence comes from the applica- tion of various analytic skills and techniques. Some of these techniques are relatively new to the marketing arena while others have been practiced by traditional direct marketers for decades in their relentless efforts to translate customer informa- tion into more effective marketing campaign outcomes.”
If there’s one thing companies learned during the recession and it’s aftermath, it’s that they need to improve the overall productivity of their marketing spend, by minimizing the vast sums of money that go to waste by marketing to the “wrong” people. Here context is king. Without context-sensitivity as a cornerstone of their marketing efforts, companies run the risk of annoying customers with unwanted and often-intrusive marketing messages. The danger is great. Failing to obtain additional business from customers is one thing. Leaving a bad taste in their mouths is another. It can be exceedingly hard to get rid of a bad taste.
When it comes to relevance and economy, no vehicle can beat email marketing. Sophisticated email marketing tools feature dynamic content delivery, making it possible to deliver different, personalized emails to customers based on their stated preferences as well as personal profile information that might include behav- ioral, demographic, past purchases and other information. Landing page creation and optimization tools are integral components of effective email marketing as is the ability to integrate with social, mobile and other channels.
The surest way to maximize ROI on an email campaign is to test and measure every component, from the subject line and the copy to timing and target audiences. Multivariate testing, which enables marketers to test several components at the same time to determine the optimal combina- tion, can show what’s working and what’s not more quickly than single A/B testing. According to Gleanster research, Top Performers not only conduct extensive multivariate testing with respect to their email, mobile and web marketing campaigns, but they refine their integrated marketing model on an ongoing basis by comparing the relative productivity of different media, channels, and tactics for customer acquisition and retention.
“Customer intel- ligence relies on not just data analytics but also data integra- tion, hygiene and enhancement. This requires the expertise of an operations team skilled in the art and science of customer data manage- ment, including the ongoing process of data integration and cleansing.”
Beyond being able to effectively coordinate channels through a unified campaign management platform, marketing improvement largely hinges on the ability to gain a better understanding of customer data, to generate customer intelligence. Invariably, customer intelligence comes from the application of various analytic skills and techniques. Some of these techniques are relatively new to the marketing arena while others have been practiced by traditional direct marketers for decades in their relentless efforts to translate customer information into more effective marketing campaign outcomes.
According to Gleanster research, nearly all Top Performers view the need to focus on customer data as a strategic imperative. Analytics allows marketers to understand the drivers of customer loyalty and attrition and determine what levers sit at the forefront of the customer purchase decision. Most large enter- prises today rely heavily on analytics in their continuous efforts to understand customer behavior at an individual level and act upon that understanding to deliver the most relevant marketing messages, offers and customer service treatments at the so-called “moment of truth.” Of course, analytics is also the basis for any customer retention program that seeks to segment a customer base in an effort to determine the most profitable category of customer.
Customer intelligence relies on not just data analytics, but also data integra- tion, hygiene and enhancement. This requires the expertise of an operations team skilled in the art and science of customer data management, including the ongoing process of data integration and cleansing. Customer intelligence also depends on the implementation of a centralized customer data repository.
The repository provides the founda- tion for creating and housing robust, multidimensional customer profiles that include such marketing mix variables as price sensitivity and channel prefer- ences. The repository also provides the basis for customer value management. Without centralized repository, a company could never know how much an individual customer spends across all of its channels, product lines and geographies, making it impossible to accurately project the lifetime value
of that customer relationship. And without a holistic view of that customer’s purchase history, stated preferences and other personal profile information, a company can never know which specific products and services to cross-sell and up-sell to that customer.
Due to the challenge of connecting their customer data silos, many companies still lack the ability to systematically identify unprofitable customers. Beyond the technology hurdle, the traditional corporate mindset assumes that all customers are profitable, which is rarely the case. Top Performers reappraise the value of their customers on an ongoing basis, either investing or divesting in those relationships that are on the fence in terms of profitability. Top Performers also focus on predic- tive modeling, which involves looking at large quantities of historic data, searching for meaningful patterns, and then creating mathematical equations that represent the underlying relation- ships within the data to forecast future behaviors. Predictive models are often called behavioral models because they may be used to predict the future behavior of a customer. By enabling companies to instantly differentiate between desirable, less desirable, and undesirable customers — and assign different marketing treatments based on their propensity to behave in a certain manner — predictive models allow companies to take actions to increase profitability. These models can rank customers and prospects from “best” to “worst” not only in terms of their likelihood to respond to a specific type of message but also through a specific channel or combination of channels.
Predictive analytics is hardly a new phenomenon. It has long existed in the form of statistical forecasting. And what is statistics but the process by which people should change their behavior after experiencing the world? Experiences may be happenstance or designed, otherwise know as experiments. Statistics tell people what actions to take in order to improve a specific process — in this case, a cross-channel marketing campaign — according to some sensible set of criteria.
Meanwhile, despite the overwhelming body of evidence regarding the value of data-driven marketing improvement, many companies continue to operate largely on instinct. Acting at a gut reaction level is certainly cheaper than conducting extensive data analyses, but only in the short run. The more profitable option is to use customer intelligence to build marketing models that seek to detect exactly how much incremental volume results from each marketing dollar spent.
Customer intelligence means analyzing large quantities of data, examining numerous combinations of variables, uncovering previously hidden relation- ships. An insurance company might ask: “What are the common attributes of customers who purchase life insurance?” Having identified these attributes, it could then score individual customers based on the extent to which their profile information corresponds with the model of, in this case, “the life insurance buyer.” Customers with higher scores might be sent a special promotion of one kind through one channel; those with lower scores might be sent a promotion of a different kind through a different channel.
“Despite the overwhelming body of evidence regarding the value of data- driven marketing improvement, many companies continue to operate largely on instinct. Acting at a gut reaction level is certainly cheaper than conduct- ing extensive data analyses, but only in the short run.”
Successful cross-channel marketing campaigns combine the science of database management and customer data analytics with the art of creative and strategic campaign development The right brain and the left brain are complementary and need to work in tandem just as the different channels are complementary and need to work in tandem. And while there are no hard and fast rules that will ensure the success of every cross-channel marketing campaign, there are some tricks of the trade that may be helpful, based on the experiences of top performing companies.
Consider four key steps: Plan, Execute, Measure and Analyze. The steps closely mirror the classic Plan-Do- Check-Act cycle, also known as the “scientific method”. History buffs can trace the scientific method to the Renaissance. Since that time, it has been adapted to numerous contexts. Yet however universally accepted, the scientific method isn’t always applied to marketing campaigns. Why not? Because society doesn’t always work based on rational economic pressures; examples abound throughout the history of human civilization. The discipline of data-driven marketing improvement is yet another example of large groups of human beings sometimes behaving suboptimally, to their own detriment.
The scientific method applied to marketing begins with a definition of the specific campaign objectives, preferably in terms that can be quanti- fied and subsequently measured using relevant performance metrics, be it clickthroughs, call-to-action responses, website traffic, incremental sales lift. Also important is the need to construct a detailed plan, including a workflow diagram, with all of the steps, including customer segmentation, target customer selection, target list generation, message development, channel selection, creative develop- ment, performance metrics, response monitoring, and so on. The planning phase also requires a set of parameters for the cross-channel marketing campaign. These param- eters might include campaign duration, campaign budget, cost per customer, break-even response rate, and target response rate for the stated goal Incidentally, an effective campaign may depend more on a response- based segmentation of customers than on a traditional segmentation based on standard demographic characteristics. Response-based segmentation starts with identifying groups of customers with similar response patterns and behaviors, and then working backwards to identify these groups based on demographic or psychographic variables. This technique uses a post-hoc approach to segmentation that relies on data to derive segments, as opposed to the traditional a priori approach that starts with preconceived notions about segment profiles and hopes to discover behavior differences. Again, with the benefit of customer intelligence, marketers are in a much better position to formulate fact-based segmentation and targeting approaches as opposed to intuition-based approaches.
Next, marketers need to test the effectiveness of the offer with both a test group and control group to avoid trial and error, and minimize risk. Tests can be conducted by offer, by customer segment, and by channel using a multidimensional matrix. Whenever possible, cross-channel campaign performance should be tracked in real time. Some problems in implementation can be detected for immediate correction while some actions can be deferred. Measuring the gap between predicted responses and actual responses is critical to analyze the causes of the gap. A simple comparison between plan and actual implementation can provide meaningful insight into campaign performance.
Because every interaction with a customer enriches the company’s information base, the next step is to use analytic capabilities to refine the process for the next go-round, thereby continuously improving marketing and service effectiveness. In the end, the key to success lies as much in capturing, analyzing and acting upon customer data, as it does in embracing a corporate mindset for experimenta- tion and campaign testing.
Cross-channel marketing success doesn’t necessarily come about merely by plugging customer data into sophis- ticated analytical models. The art of creative development is as important as ever. The challenge is to marry the art with the science. The tactical aspects of cross-channel marketing campaign execution, including target audience selection, channel selection and campaign duration, as well as such key parameters as target response rate or sales lift for the stated goal, should always be driven by business objectives. Creative develop- ment should then flow naturally from these decisions.
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