FROM BROADCAST TO COLLABORATION
In the last chapter, I built the first proposition, showing how big data gave us a lot more observations about customers. This rapid rise in data has also been coupled with an equally rapid advancement of advanced analytics and automation to drive marketing decisions. The market leaders foresaw the availability of big data and started to build gigantic receptacles to contain and control the big data tsunami to their market advantage. A large number of consumption options have fueled the need for real-time and intelligent decisions, which must be automatically generated and fed into the consumption engines. A number of these advancements discussed here are very disruptive to the market, as they are driving significant automation and disintermediation of the middlemen, who processed and massaged the data. They are tearing apart marketing as we knew it in the past and replacing it with a new set of actions.
I continue to receive nearly five to ten promotions from credit card companies per week in the mail. Each of these is an invitation for a new credit card with lucrative sign-in bonus miles or other goodies. As I toss those offers unopened in the trash, I sometimes try to estimate the cost of these campaigns and imagine their intake reports. Is anyone with my profile using these promotions? How can the credit card companies improve their yield? It so happens, like many other empty nesters, I have no need to shop for credit cards. Each time I switch credit cards, my credit rating companies reduce my credit score, and I need the best scores to keep my mortgage rates low. Last but not the least, I have not used any of the offers provided to me via mail, ever! Do they not have a way of tracking a completely disinterested prospect? Maybe I am not the best target for these promotions? Can they track my response and improve their campaign yield?
Marketing organizations have traditionally broadcasted their campaigns to customers based on their analysis and understanding of segments. As long as a reasonable proportion of customers from the target population was reacting favorably to the offers, marketers kept investing in the rest of us, filling mailboxes and wastebaskets with promotions that were never read or acted upon by consumers.
The early evolution was in the use of analytics for segmentation. The original segmentations were demographic in nature and used hard consumer data, such as geography, age, gender, and ethnic characteristics to establish market segmentations. Marketers soon realized that behavioral traits were also important parameters in segmenting customers.
As our understanding grew, we saw more emphasis on micro- segments—specific niche markets based on analytics-driven parameters. For example, marketers started to differentiate innovators and early adopters from late adopters based on their willingness to purchase new electronic gadgets. Customer experience data lets us characterize innovators who were eager to share experiences early on and might be more tolerant of product defects.
In the mid-1990s, with automation in customer touchpoints and use of the Internet for customer self-service, marketing became more focused on personalization and 1:1 marketing. As Martha Rogers and Don Peppers point out in their book The One to One Future, “The basis for 1:1 marketing is share of customer, not just market share. Instead of selling as many products as possible over the next sales period to whomever will buy them, the goal of the 1:1 marketer is to sell one customer at a time as many products as possible over the lifetime of that customer’s patronage. Mass marketers develop a product and try to find customers for that product. But 1:1 marketers develop a customer and try to find products for that customer.”1
Social media created the next wave of changes, which significantly improved consumer power through collaboration. Consumers started to collaborate—first for social reasons, but then to compare notes on marketers. Yelp created the crowdsourced rating system in which consumers can share their experiences. Amazon started to pay attention to the most influential reviewers who changed the opinions of others. Facebook started as a social media site first, but then gradually opened its vast customer base to marketers.
Fast-forward to today. Campaign delivery capabilities have improved significantly. With online purchasing gaining critical mass, there is a need and an opportunity to use marketing at electronic point of sales at silicon speed—in milliseconds. These marketing capabilities are fueling three significant improvements in marketers’ ability to influence customers and vice versa. First, marketers are able to use predictive modeling and social media to find the customers best suited for their campaigns. Unlike reporting systems of the past, sophisticated predictive models mine the data to target specific customers and sharpen the messaging to them. Social media offer ways to organize customers and offer customer groupings to marketers. The second improvement is in our ability to develop marketing actions at high speed and use them to influence targeted customers in real-time or on-demand. These actions can be delivered to specific customers or micro-segments. Third, is our ability to collect customer reaction to a focused campaign and fine-tune the campaign based on the reaction. It allows the consumer to influence marketers. By providing a “thumbs up” to an advertising message, consumers can communicate back to the marketer, their interest in the subject area. These three improvements—micro-segmentation, focused messaging, and customer feedback—provide the necessary pillars for collaboration between marketing and customers and drive influence in marketing campaigns.
Marketers have used a variety of ways to influence customers. In this chapter, I will focus on a number of these marketing capabilities and show how they are bringing dramatic changes to marketing capabilities in order to reach and influence customers. I will cover their impact on product design, advertising, promotions, and pricing.