In an increasingly dynamic economy, companies must generate sales growth as a result of marketing investment. No longer can marketing only be focused on “brand-building” and awareness – companies will not succeed if they squander limited marketing resources on misdirected campaigns and interactions. Time and again, I see that the leading companies are those where marketers are managing customers and prospects in real time, across channels, on a personalized basis. They have succeeded because they are proponents and practitioners of data-driven marketing.
Marketers are increasingly expected to develop a deep understanding of their customers and to leverage this intelligence to increase revenues and profits for the organization. They are also expected to collaborate effectively with other functions within their organizations, particularly sales, customer service and even product innovation and supply chain.
The challenge in marketing today is that many organizations are still utilizing antiquated, outdated and inflexible marketing business processes supported by inadequate tools, marketing mix models, and agencies that lack the ability to integrate and provide analytics / insights on multiple disparate sources of consumer or customer data.
Additionally, it can be a challenge to measure marketing investment performance across multiple channels (vs. the traditional mass media channels) and marketing business processes are often fragmented and span departments and agencies. There is a plethora of new structured and unstructured data that may be perceived as a “positive” but only if integrated and actionable – many marketing teams are overwhelmed by customer data and incapable of transforming the data into valuable customer insight.
These challenges, however, can be overcome. Many customer-focused organizations have taken the steps necessary to develop customer intelligence and data-driven marketing techniques. Marketers in this category are utilizing customer insights to allocate marketing investments, are targeting marketing messages based upon both value and likelihood of acceptance, are implementing a strategy to coordinate campaigns, marketing messages, and branding at every customer touchpoint, are calculating campaign effectiveness rapidly, and are consistently improving their marketing processes by incorporating lessons learned into the model.
A Data-Driven Marketing strategy fuels all aspects of integrated and interactive marketing:
- Integrated Analytics – Analytics allow marketers to understand customers, allowing them to react to opportunities, trends, and patterns and to build more targeted and relevant communications. As such, analytics are a critical component of a marketer’s toolset. By having analytics integrated with the marketing process, marketers are able to build and execute campaigns dramatically faster than those created using solutions sourced from multiple vendors. Such improvements are possible only in an integrated solution, and they enable marketers to use campaign velocity as a weapon. The faster an organization can move through the closed-loop process, the faster it will get results and learn what works (and adjust from what doesn’t work in a campaign). Higher campaign velocity creates the ability to execute more frequent—and more highly targeted—campaigns, and it means the organization can react to new opportunities before slower competitors. Integrated analytics also increase the accuracy of campaigns, ensuring that marketers reach the right customer with the right offer. Moreover, they enable proper closed-loop analysis so marketers can learn from each interaction. The benefits are higher response rates (resulting in more revenue), lower costs (since fewer messages are required), and fewer wasted customer contacts.
- Campaign Measurement— a data-driven marketing strategy provides direction for marketing investments based on customer value and expected customer value. Resources are shifted away from immeasurable and unmanageable mass campaigns and towards initiatives that promise a clearly defined and provable impact on the bottom line. It also enables learning from previous campaigns and customer interactions, and supports utilization of the resulting information to refine future campaigns.
- Customer Relationship Growth—A data-driven marketing strategy leverages customer insight to develop intelligent plans for customer interaction, leaving no interaction to chance. It enables organizations to optimize every interaction in real time and to react to changes in customer status to ensure that every marketing communication moves the customer to the next desirable step in the relationship.
- Customer Conversation Evolution—A data-driven marketing strategy treats customers as individuals, and manages each customer relationship during every interaction across every touchpoint. This conversation ensures that a dialogue with a customer resumes where it was last left and continues it in a way that is personalized. The organization may then present a single view to the customer regardless of interaction channel.
- Customer Acquisition—A data-driven marketing strategy leverages customer knowledge to guide marketing investments and thereby generate the maximum return on customer acquisition efforts. Customer acquisition is key to any growing organization and is an imperative given the fast-moving consumer preferences and behaviors.
- Multi-Step Campaigns – In a multi-step campaign, every customer interaction is recorded and expanded upon in subsequent interactions, regardless of touchpoint. While many organizations treat customer interactions as independent events, data-driven marketing organizations recognize that customers view their interactions as part of a single, continuous conversation with the brand or larger organization. Such organizations recognize that they must manage interactions across channels and touchpoints, departments and functions, distance and time. Companies that fail to do this will create a fragmented customer experience, ultimately leading to reduced customer loyalty.
Teradata: Justin Honaman
Title: Managing Partner, Consumer Goods / Retail North America Analytics Practice Leader
Twitter: @jhonaman @teradataCPG #teradata