Data-driven analytics and customer insights are rapidly becoming the cornerstone of the modern marketer. Today’s capabilities reach well beyond traditional segmentation and campaign ROI. Savvy marketers are combining information from digital channels with past behavior to fashion extremely personalized communications, redefining the long-touted “segment of one” into a set of contextualized, real-time responses that meet customers in their “moments of now”. And it is paying off handsomely. Participants in a recent Forbes Insights study enjoy benefits from insight driven journey management that range from traditional measures such as profit, sales growth and ROI, through to organizational improvements including faster decision making, increased confidence in analytically driven decisions, and better collaboration between business units.
To see how you are doing and identify your aspirational next-steps compare your company to the best practices of industry leaders in these four critical customer insights and analytics areas .
Customer Insights: Value. To what extent are you using analytics to develop insights about customer value, and how are these insights operationalized?
The Evolving Company: We evaluate revenue and costs in detail at an individual level, incorporating techniques such as activity-based costing. Analytics are used to extend customer profitability to predict lifetime value (LTV). Customer profitability and LTV are used across a variety of business processes such as customer service (key decision/ recommendation input), channel evaluation (channel effectiveness, experience management), product development (feedback) and marketing (segmentation, campaign targeting).
The Progressive Company: We understand the customer’s influence value within their particular social and community networks. We also have a high-level view of the value of the networks themselves. These factors are used to extend (or override) the more traditional profitability and LTV scores. The organization as a whole understands the impact of LTV and social advocacy to overall brand value and these are factored into most business processes.
Customer Insights: Behavior. Are you developing insights around customer behaviors (product and channel usage, lifestyles), and are you using them to enhance the customer communications?
The Evolving Company: We are using off-line analytics to establish normal behavioral patterns (e.g. scale of significant transaction types, behavioral trends) for each customer across the range of products they own. We can evaluate incoming or recent transactions against the norms to determine the significance of a particular transaction (significantly greater or less than “normal”).
Triggers may be set to send notifications out to some of the channels when customers stray outside the thresholds of individual or combinations of specific thresholds. There is some real-time triggering happening today, but much of the activity is after the fact.
The Progressive Company: Customer behavioral analysis and feedback captured during inbound interactions are used in conjunction with offline data and analytical models to drive real-time sales and service recommendations within most or all interactive channels. We are using the insights to personalize the customer experience personalization in order to improve response rates and customer satisfaction. Complex customer interaction processes can be tracked and managed coherently across multiple channels over time.
Customer Insights: Attitudes, Opinions and Sentiment. Are you using sentiment and social network analysis to develop insights around attitudes, opinions and sentiment? How do these insights influence customer interactions?
The Evolving Company: We run proactive, structured, internally-focused programs designed to capture detailed feedback on customer opinions and satisfaction levels and to provide detailed analysis and predictive models. We conduct high-level research into external opinions and satisfaction levels by analyzing commentary expressed via social media channels, although this is largely a manual, ad-hoc exercise.
The Progressive Company: We have an automated, highly-structured program of social media analysis which includes opinions and sentiment expressed around specific topics (e.g., product features, pricing, service, distribution) with respect to both the organization and its key competitors.
Sentiment data gathered is directly associated with known customers in the marketing data store. We synthesize customer sentiments with operational interactions in real time to optimize not only the content but the flavor and tone of the interaction.
Analytical Model Usage and Management. Does your organization make use of analytical models in marketing efforts? How do you ensure that the models used are fresh and current?
The Evolving Company: We have a wide range of analytical models addressing many stages of the customer lifecycle (e.g., acquisition, development, retention). Models are run regularly and results are available to the campaign teams. We may have the capacity to execute some of our models directly from a marketing automation application as a part of the campaign list development process. The model development and maintenance process, including communication between analysts and business, are largely manual. Some model modifications do take place—albeit without formal evaluation guidelines.
The Progressive Company: We use advanced techniques to model complex combinations of factors (e.g., purchase propensity and value for combinations of content, price, channel and offer by customer). Our models support channel efficiency analysis, performance evaluations and real-time decision making efforts and are employed directly in most inbound and outbound campaigns.
Models are managed strategically in a central repository and are automatically retrained on a lifecycle that is appropriate to the volatility of the data. We employ a test and learn approach to all model changes.
Didn’t make the chart? Then your marketing group is probably nascent. Because nascent companies tend to have less focus on analytics, starting a program of education on the value of analytics and fact-based decision making that includes marketing, as well as key executives, is recommended. Transitioning beyond profitability and behavioral analysis that focus purely on product usage and ownership to look more holistically at customer relationships is a good first step. Evolving? The next step for you might be to transition manual ad-hoc social network analysis into repeatable activity where results are used to impact customer experience. Progressive? Congratulations! Progressive companies use advanced predictive modeling techniques to determine an extended view of customer profitability which includes influence value across social and community networks. You can stay on top by continuing to use detailed behavior and social media analysis to shape customer interactions in real time.