Great data comes with greater responsibility

As Albert Einstein once said, “in the midst of every crisis, lies great opportunity.” While the internet becomes more privacy-centric & demise of tracking third party & device ID, the role of data becomes increasingly important. Unlike third-party data, which is collected by aggregators and ad platforms through third-party cookies and unpleasant tracking methods, FPD (first-party data) & ZPD (zero-party data) are collected willingly and directly from customers. Zero-party data, a term coined by Forrester Research, is also referred to as data that a customer intentionally and proactively shares with a brand. It can include preference, purchase intentions, personal context, and how the individual wants the brand to recognize them. Think of the kind of things you’d say to an ice cream parlor associate helping you prepare the right box of ice cream for your family — size, flavor, budget, texture, eating habits, packaging, etc. That’s zero-party data for that ice cream parlor & next time when same customer walk-in or order online, the ice parlor have enough data points to customize the order. First-party data on the other hand is every data about the customer that a company collects from both online and offline sources, such as the company’s website, subscription, CRM, social media, or surveys. When you submit your email address or phone number to the news/business website to access premium content to read, you just provided them with first-party data. The first-party data can include deterministic data such as Device ID, email ID, and probabilistic data such as demography, time spent, purchase history, and so on. Privacy concern around FPD & ZPD is very minimal because of audience consent & it also delivers quality insights into the audience to create a personalized experience, improve retargeting strategy & predict future trends.

Why should Data Strategy matter to Marketer?

Companies need to have their own data strategy and start acquiring data to provide a richer customer experience. According to Forbes, “Over 90% of consumers say transparency by a brand is important to their purchase decisions.” Transparency is so vital that “94% of all consumers are more likely to be loyal to a brand when it commits to full transparency. You will have to gain customer trust through transparency & value exchange needs to be clear. There are multiple ways by which companies can capture data and one of the best ways is to use loyalty cards. Take an example of a shopper stop that encourages its customer to use a loyalty card when they make a purchase, so they can obtain their purchase preferences once they check out. Value exchange between a company & its customer is transparent as the customer gets purchase points that can be utilized in their next buys. Customer data can be collected in both online and offline environments & some of the ways to acquire are surveys & polls, loyalty programs, opt-in forms, email preference centers, single sign-on (SSO), progressive profiling, warranty, or product registration, feedback & reviews. Direct to consumer (D2C) brands can easily add a pixel to their website & apps & user behaviors data are pulled from landing pages, apps, CRMs, social media profiles, subscription-based emails, customer feedback, user surveys, and other locations. Before companies start acquiring data, they need to ask themselves why a customer will give you their information without a good reason. There typically needs to be some value exchange that incentivizes filling out a form or providing an email address or phone number. These value exchanges can be anything like exclusive content or newsletter access, discounts, exclusive customer support which are not available to walk-in users.

There are quite a lot of industries where collecting customer data can be an uphill task because of dependency on OEM or dealer structure & even if you collect data needs to be constantly preserved, improved in quality and enhanced with additional attributes/identifiers. Companies shall be agile to acquire data from other companies which is called 2nd party data. Second-party data is basically another organization’s first-party data, as they gather it directly from their audience & no data aggregator is involved. Let’s understand this with an example if you run a fintech company that deals in mutual funds & bonds, and you want to find out who you should target for commodities & currency trading. You could talk to a publisher who creates and shares content related to currency & commodities & acquire their first-party data which acts as second part data to your organization. This information will tell you which types of customers are most likely interested in currency & commodities trading & then you can create customer cohorts & target ads to bring them to your fintech app. You can discover 2nd party data in the data marketplace & it works like any other marketplace where a buyer finds a suitable seller and buys audience segments. When you use 2nd party data segments from trusted partners or private data marketplace, the quality is good, so you can easily use it to reach out to your new customers.

How to use Data for personalized marketing activation?

Collecting data is just half the battle & companies needs to think of storing & enriching those data to drive data-driven marketing. One of the easiest ways to activate data-driven marketing is uploading your CSV/excel file of data on walled garden platforms like Google & Facebook. Facebook custom audience or Google Customer Match is an example of one such function which allows advertisers to serve ads based on data shared with these platforms. Customer Match or custom audience lets you use your online and offline data to reach and re-engage with your customers across different digital platforms in the case of Google it will be Search, Shopping tab, Gmail, YouTube, and Display & in Facebook, it will Instagram, FB, messenger & so on. Using information that your customers have shared with you; such solutions will target ads to those customers and other customers like them which is also called look like modeling. The same model can be used on other Demand side platforms like Trade desk, criteo to target audience or lookalike audience beyond walled garden platforms. Additionally, data can be activated by using a process called Data onboarding by transferring offline data to an online environment. Data onboarding companies like LiveRamp or Neustar are mainly used to connect offline customer records with online users by matching identifying information gathered from offline datasets to retrieve the same customers in an online audience for example a customer’s email address or postal address can also be used as an identifier to match to digital ID’s, such as a Facebook or Twitter account. Whichever way you are collecting your data it needs to be compliant as per country data law & regulations.

Customer data collected & stored in a CDP/DMP without segmentation is mostly useless. Data to value a business needs to be actionable, value-adding, and easy to understand—exactly what data enrichment offers by creating user segments & cohorts. Data enrichment is the process of integrating new updates and information to the existing database by combining it with 2nd party or 3rd party datasets. There are several ways to do data enrichments like demographic & geographic. Demographic data enrichment is the process of enriching an existing dataset with demographic information, such as marital status and income level while geographic data enrichment is the process of adding geographical data to an existing dataset and can provide insights: from postal codes to geographic boundaries. There can be other ways like purchase intent data enrichment & App usage-based data enrichment as well. Data enrichment allows businesses to stay relevant & when messaging is personalized it not only improves customer relations but also shows users that you care about their needs and understand them as clients.

Don’t take data as a remedy; take it as a stimulus!

Companies need to be responsible with data-driven marketing & look around the business like Netflix & Spotify who has built a reputation for using data to create highly personalized consumer experiences. Data always matter however will suggest my clients not be data-obsessed marketer & take risk & a leap of faith with creativity and messaging. Data has finite scale, due to the lack of information about factors outside of the existing base, hence difficult to scale marketing strategies for continued reach & growth. New age marketers shall bring data, creativity & social listening together & use this to launch the next “big idea “& not limit themselves to doing campaigns only on the collected databases. social listening can help discover prospective marketing & product ideas. The creative team needs to know data so they can customize messaging to the distinct cohort of customers & the data team needs to understand creativity so they can convey insights from the data. In marketing, you don’t need to choose between data & creativity as they will work together to develop effective marketing strategies.

About the author :

Prashant Nandan, Principal Partner – Client Leadership, Mindshare