Double down on your first-party data strategy to be future-ready
Capturing transaction data is step number 0 in most organisation’s first-party data journey.
Data, data everywhere. There's data everywhere you look today. From smartwatches to supermarket scanners, and from online user behavior to advertising data, companies are rich in information. Of course, not all types of data are created equal and first-party data still reigns supreme. First-party data has regained its glory, so to speak, in the light of the announcement made by Google to deprecate third-party cookies.
This article would be relevant to the leaders who obsess over customer loyalty in B2C industries and are planning their first-party data strategy to deliver great experiences to their customers and maximize their customer value.
As a preamble to define first-party data, it's the data an organization collects on its customers via the organisation's interactions with customers. As an example, for a retailer this data would include the demographics, transactions, inbound interactions and outbound communications at the customer level.
Most organisations have technology in place to capture transactions data. Staying with the retailer example, the organisation would have POS (point of sale) systems in place to generate a receipt, which includes information on the products, quantity, price-points, discounts, coupons, store info, date, time and the check-out associate. This is what we would consider as ‘basics' because as a retailer, you need this information to run your operations; meanwhile, customers need a receipt of purchases for their own records.
Capturing transaction data is step number 0 in most organisation's first-party data journey. It's what happens next that determines which organizations become ‘stand-outs' from the crowd. In this article, I outline the four critical steps organizations can take to build richer first-party data over time.
Step 1: Improve your customer identity
Many retailers would ask for a phone number at the time of check-out. Some customers give out this detail for a promise of loyalty and points; some customers do not give out their phone numbers easily; some customers may have more than one phone number. Does the retailer fully understand the identity of their customers?
In a striking example, a CPG company realised that roughly 10% of the consumer IDs in their database are duplicates. An identity resolution solution helped them to aggregate multiple customer IDs into one. Imagine the amount of marketing efforts saved in targeting the same consumer multiple times assuming that those are different individuals.
So, solving for customer identity becomes a critical first step in your first-party data strategy. Building and/or investing in an identity resolution becomes a necessity so that you can roll-up multiple transactions at a single customer level and build a comprehensive transactions view on the customer.
Step 2: Invest in knowing your customers
Once you have solved the customer identity problem, enriching the understanding of your customers is the second step in your first-party data strategy. There are multiple options available including mining your own data, getting supplemental data from third-party data providers, building second-party data partnerships and investing in adtech solutions.
In data rich environments, organisations can hire specialist data scientists to mine data to develop a richer understanding of the organisation's customers.
Then there are data partners who can provide additional data on your customers. This may include data around house-hold makeup, life stage, lifestyle, automobile ownership, home ownership, credit risk etc.
There are second-party data partnerships that can be mutually beneficial between the organisations. For example, a grocery retailer would be willing to share customer insights to an FMCG (fast-moving consumer goods) brand for the brand to invest in a targeted media promotion through the retailer.
Then there are adtech solutions (e.g. Customer Data Platforms) that can help an organisation learn more about a customer or a prospect who visited the organisation's website or downloaded an app. This information may include browsing categories, media consumption, device info, location etc.
Step 3: Tune in to inbound customer interactions
Customers may reach out to the organisation for inquiries and complaints – calling the call centre, sending an email or using the chatbot on your app or website.
Are there mechanisms in place to record the interactions data at the customer level? Often times, the systems that record customer inquiries and complaints belong to a different department within an organisation (e.g customer service) and sit outside of marketing team's purview. This could lead to a classic example of siloed data. This data could be immensely useful for marketing and customer engagement if it was brought into the fold of single customer database.
For example, an insurance company realised that some of the ‘signals' on policy surrender inquiries generated from mining their customer service database were really powerful in their retention initiatives driven by their operations team.
Step 4: Listen carefully to how your customers respond
Marketers often have a calendar of planned marketing activities, and they have a choice of owned, earned and paid media channels to reach their customers and prospects. It's useful to ask how much of this marketing communications data is captured and at what level of granularity.
Customers provide a rich set of information by choosing to engage with or ignore the marketing communications. This information needs to be captured as part of efforts to learn more about our customers and their preferences.
A retailer used an inventive combination of owned media (email) and paid media (programmatic display) to generate incremental sales from their customer base. They started with sending email communications and followed that up with targeting only the subset of the customers who landed on their websites and apps through a paid programmatic media targeting. This resulted in a higher return on their marketing spend compared to their previous paid media campaigns.
This is all great! What about customer privacy?
We cannot conclude any discussion on customer data without addressing the privacy question. Organisations that collect, store and process customer data have an obligation to uphold the data privacy of their customers. This also makes the marketing more purpose-driven and ethical, keeping consumers' interests at heart. In markets where customer data regulations are still being drafted, it's important for organisations to follow the best practices from other developed markets (e.g GDPR in Europe and CCPA in California).
Here are some simple rules to keep in mind:
- Ask for customer consent to be part of your programs (CRM, Loyalty, etc.) or to receive your marketing communications
- Be transparent and open about how you intend to use their data and how that would benefit them
- Give options to your customers to see what data you have on them, and give them choice to manage their preferences
- Respect opt-outs from your customers
- Purge the dated customer data no longer required
It usually takes a few months for organisations to put together their first-party data strategy and roadmap, but it takes years for them to execute those strategies. This is more due to higher level of complexity associated with leadership vision, alignment and organisational dynamics than the technology requirements.
Having said that, the ‘stand-out' organizations across industries have transformed themselves through a data-driven agenda. It is never too late to execute on your first-party data strategy and reap the benefits for years to come.
This article has been written by Lakshmana Gnanapragasam, VP-Analytics for APAC & MEA, Epsilon
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