The use of Data in digital marketing is no different than the use of data say in other aspects of the organization - help solve problems.
The key problems for a marketer primarily stem from:
- Finding out what sticks, what doesn't - Experimenting with key drivers of campaigns (messaging, targeting, are we getting people warmer or colder to the idea of buying, why?)
- Eliminating Wastage - Optimisation as some people call it, don't throw money and time away - finite resources we can't afford to lose
- Identifying opportunities and trends (both decreasing and increasing occurrences ) that warrant more zero-ing into over time (Note this has a time element and comparison to it).
The key dimensions marketers dive into form the base of a framework to help answer the following questions related to the above:
-Who, When, Where, What, How, Why?
Does the 'buy one get one free' offer work better to retain churn or does it work better with getting new customers? When should we do this? How do we do this - do we sent app notifications or drive remarketing with customer audiences?
In being able to answer basic questions like these, we need to know where we are able to find these data points and which tools we should focus on?
The most crucial part of the process is to map your entire business funnel and identify key points of the funnel which are being tracked, if there are gaps, devise proxy or mechanics (eg coupon code) that help gauge performance. In the real world where offline and online buying considerations are hard to determine, this is important to do so. We can explore this in another article but for now let's focus on the key data points one needs to work with.
- Paid Advertising - Facebook business manager, Google Ads Manager and Ad Buying Platform reports.
- Firebase or GA Web+ App for App analytics -This is the mobile app tracking equivalent of Google Analytics.
- Backend Shopping Cart Data (If there are e-commerce transactions) - Shopping cart (eg. Shopify, Magento, Woocommerce, Opencart etc) data usually cover detailed crucial 1st party information of transactions (people who have purchased) including customer details, addresses, products purchased and when they were made. Some carts do collect 1st party data (including email sign ups and registrants who may not have purchased). The key difference between Google analytics or web analytics with backend cart data is web analytics data do not usually have actual customer or user information tracked and stored (PII reasons unless matched subsequently, this also depends on privacy laws in specific jurisdictions). Also backend cart data do not have granularity in events or behavioural or browsing/search term data that indicate intention including pages read, time on site etc which are key in establishing predictive or labelling/scoring of users. It is advisable to stitch or join these together for full customer/transaction level analyses - this is the basis for a 360 degree of the retail customer.
- CRM data (lead generation) - CRMs serve as a repository for lead generation campaigns where lead information are kept and tracked for progress up to them turning into customers. This data (just like backend cart data) tracks detailed 1st party customer data in terms of what services/products they are interested in, intention, status in the buying process.
- Marketplace Data - For companies who sell via marketplaces including Amazon, Lazada, Shopee, Farfetch etc, customer data are also important if they represent a large part of revenues or for many a source of customer acquisition.
- Loyalty/Offline platforms - Retailers and ecommerce (including companies with direct to consumer relationships) usually invest in systems to track and manage customer relationships usually via some sort of loyalty system where 1st party data (name, email, phone numbers) of the customers are collected and tracked to build stronger buying relationships with customers. Very often these tools also have communication functionality and points tracking including emails/mobile app messaging. Tracking this information in tandem with the ecommerce or online platforms is absolutely crucial to derive insights on omnichannel behaviour.