Every day customers take advantage of different channels to research and purchase whatever they need, from personal items to business products and services. Often these ‘buying journeys’ involve more than one channel, with digital channels growing in usage whether the purchase is made online or in a brick-and-mortar store.
More marketers are working to better understand customer buying journeys, which can be complex and hard-to-predict simply because of the high variability for how customers arrive at buying decisions. Another objective is to gain more intelligence regarding how customers are influenced by overall interactions with a company, before, during and after purchases. Marketers also need to know more about diverse external influencers that can play significant roles for buying processes (“influencers” aren’t always people…).
Each customer pretty much calls the shots while on most buying journeys. Companies should be working hard to provide what is potentially needed at each touchpoint along the way; such work can be made more effective if handled with the customer perspective at top of mind. Companies shouldn’t get in the way of the customer taking the journey, but should make it ‘easier’ for customers to find what they’re looking for and to make purchases. So organizations are striving to provide the right information and support at the right time on the right device and the right channel to nurture successful outcomes to buyer journeys.
Marketers need continuously updated and comprehensive views of customers and prospects, either as individuals or as segments, to improve communications and support during the buying process. New marketing technology advances such as marketing automation and adaptive marketing require very precise customer intelligence. Many information sources for advanced analytics fall into the ‘big data’ category, which requires specialized skills and analytics processes.
McKinsey analysts have shared interesting research on the ROI of big data analytics for marketing functions:
McKinsey analysis of more than 250 engagements over five years has revealed that companies that put data at the center of the marketing and sales decisions improve their marketing return on investment (MROI) by 15 – 20 percent. That adds up to $150 – $200 billion of additional value based on global annual marketing spend of an estimated $1 trillion.
Using agile and comprehensive analytics to derive accurate intelligence for customers and buying journeys is only part of the story. Engendering real engagement and positive interactions is equally important. Personal – and personalized – interactions and experiences must be energetically nurtured and supported. Worthwhile rich content must be continuously generated, with individual customer segments as clear targets. It’s still Marketing, where creative processes are essential – but now more than ever, marketers need to be ‘data smarter’ so as not to squander valuable (and frequently expensive) creative activities.
While analytics and accurate customer and product intelligence are of enormous value to marketing and sales, marketing groups in many organizations have miles to travel before they have enough people with the right skills to understand and work with analytics. (The same can be said of many other business functions that can benefit from advanced analytics.) An InformationWeek article recently stated that “More than a third of executives rank big data analytics as a top marketing skill, but many marketers lack the requisite knowledge”:
This change in the required skill set … has created a challenge for marketers as 45% of executives now view marketers’ limited competency in data analysis as a major obstacle to implementing more effective strategies — second only to inadequate budgets for digital marketing and database management…
Marketing investments for working with all sorts of data sources through sophisticated analytics processes can bring big dividends to the entire enterprise. Customer and product analytics and intelligence results must be shared across the enterprise: customer service, product strategy and development, corporate strategies, and financial planning. In this sense, marketing analytics should be a whole enterprise investment and obviously a strategic initiative from top to bottom.