The center stage of Data-driven marketing: Consumer experience
The original premise of marketing has always centered on two objectives. First, to find out customers’ needs and desires, & then, using that insight to deliver what customers wanted to purchase. Data-driven marketing has just added essence to this by understanding the customer data you already have, the data you can find, and how to consolidate, evaluate, and utilize that data to improve marketing efforts.
As per TRAI India will have close to 850 million internet users by end of 2021, and with this scale, the quantity & variety of data have just exploded. While the emphasis on customer data remains strong, the subsequent marketing efforts are only as good as the quality of the data behind it. Unfortunately, many brands continue to grapple with the challenge of outdated data, missing information, and data siloes. Data-driven marketing connects the three essential dots, Creative which is the message, data which is who you want that message to be delivered to & media is where you want that message to appear.
Consumer experience is key to this equation & consumers don’t want companies to know everything about them. As per HBR Report Consumers believe strongly about data transparency, with 79 percent of customers stating that they will stop doing business with a company if they learn their personal data is used and collected without their knowledge. Consumers are worried about how organizations make use of their data – ranging from intrusive messaging to the risk of having their data stolen. Brands must be highly transparent with what data they are collecting, how they will use that information, and how it will be stored and secured. Customers should have control to change their data or to delete their account as per GDPR Law. Consumer data that companies are using is termed deterministic & probabilistic data. Deterministic data is data that is known to be authentic; it is based on unique identifiers that match one user to one dataset like email id, phone number, or customer ID. Probabilistic data is based on relational patterns and the likelihood of a certain outcome like location data, behavioral data & so on. Brands find themselves at a data strategy crossroad of which data to use & the correct approach or both. While the gold standard of data-driven marketing is deterministic data, it is hard to scale after a point of time & if you need more customers who are interested in your product or services you shall add probabilistic data sets. In today’s DNA of data-driven marketing, companies need to have a reliable data management platform that will enable customer data to be integrated from all channels to help inform highly targeted and personalized advertising and marketing campaigns.
As per the salesforce report, 80% of customers value the brand experience as much as the product themselves & that is why an organization needs to understand the importance of owning data management platforms like CDP & DMP. CDPs or DMPs, are frequently confused with each other & are CDP vs DMP, an either-or situation, but that is not the case. Customer data platforms (CDPs) work with storing ‘Personally Identifiable Information’ such as names, postal addresses, email addresses, and phone numbers, while Data management platforms (DMPs) work almost entirely with anonymous data sets such as cookies, devices, and IP addresses & anonymized first-party data. CDP can store all sets of data including 1st, 2nd 3rd, or zero party data hence it can be used on all aspects of marketing & communication while DMPs are primarily used for advertising only. Let’s understand DMPs & CDPs by example, Facebook & Google are a good examples of large DMPs, they have billions of customers, collect data of those customers, anonymize it, and sell it to advertisers. Swiggy & Zomato uses CDPs to collect and organize data from the users on their website, mobile app, or anywhere else someone might interact with their business. They are taking the data collected by CDP and sharing it with their Martech stack for SMS or email marketing to one or many segment of their audience. Another big difference between these two platforms is how long each of these platforms can retain data. Most CDPs give their users the ability to retain customer data for a long time. CDPs even let the user set limits on how long their customer’s data is held, and many CDPs allow their users’ customers to request access to or deletion of their data. For example, swiggy & Zomato using CDP platforms can run promotional campaign to give a 25% discount to your most valuable customers from the past year. They will just go back to CDP & check transaction data of customers who spend most of the money with the company last year and run a 25% discount campaign only for them. DMPs are the entirely opposite. For example, Google & Facebook only retain data for a short time — 90 days is common in advertising. Reason for it: If you’re an advertiser looking to target people interested in travel, you don’t want to target someone who was interested in travel a few years ago. You want to target people who are interested in travel right now which is also called in-market audience or have been interested in the past 90 days, at most.
Both CDPs and DMPs can be very valuable platforms and companies need to think about their goals & situation they are in before deciding; they need both or one of the platforms. There are differences between DMPs and CDPs, but they are not competing technologies; they are already complementing each other. For example, Siwggy & Zomato can push their CDPs data into Facebook & google data management platforms to improve the accuracy of their look-alike audiences. Once they have attracted that customer to their site/app, that is when the CDP can take over, providing real-time personalization.
Building an incredible consumer experience is an art & science and you need precise data to uncover areas that need improvement. As per consulting firm Frost & Sullivan consumer experience has already overtaken price and product as the key brand differentiator. Concentrating on customer experience diminishes the cost of customer care as a happy consumer are much less likely to return products or demand a refund. They make fewer calls to customer support & provide positive feedback on social media and other platforms. In the data-driven world that we are living, consumers tell us what they want, and how, where, and when they want it than the traditional approach of marketers messaging or emailing customers what they thought they wanted. Data & Analytics is helping brands transform their customer experience; the more you can customize the interactions and see where you can remove friction from the consumer experience, the better it is for the organization.
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About the author :
Prashant Nandan, Principal Partner – Client Leadership, Mindshare