Dr. Jekyll & Mr. Hyde: Data Resolution in Marketing

Wrestle the gusher of customer data into making you money

In The Strange Case of Dr. Jekyll and Mr. Hyde, the main character is split between two personalities that come out at various times after taking a personality-splitting potion.

Signet Classics cover art for Dr. Jekyll & Mr. Hyde

He is the moon-less version of a werewolf.

Dr. Jekyll is a respectable, mild mannered doctor who works hard to suppress evil urges that he feels.

Mr. Hyde is a cruel, remorseless criminal who lives out the evil fantasies that all people keep locked below the surface.

They act completely differently.

They’re so different that townspeople mistakenly believe that Hyde is blackmailing Jekyll.

It takes time for the people in the town to realize that the vastly different behavioral profiles are embodied in the same man.

The story only comes to a (grim) resolution once people understand that Jekyll and Hyde are the same person.

---

Customer Data Is Useless without Structure

You’ll often hear that “data is the new oil” in marketing & analytics.

The palpable excitement from a CMO when a new customer channel is unlocked is the same excitement as a prospector hitting a gusher.

The Lucas Gusher at Spindletop, Texas (1901) [Source: Wikimedia]

Crude oil is only useful once processed and refined; business data is the same.

Trying to train AI/ML models on unprocessed data streams will result in very computationally expensive garbage.

How should we structure data then?

First, check out these articles below to understand what customers are telling you and how to keep track of them.

---

---

Once you understand the kinds of data that exist in the market, the next step is to make sure you accurately unify & resolve¹ data to the level that makes sense for your analysis.

A few common levels of resolution could be:

• The geographic level

  • This level consists of products consumed at the geographic level. It does not matter if a single individual loves or hates these products if the general sentiment of the population is not in line with them.

  • Examples: Utility services, sports franchises

  • A utility should consider doing analysis by geography. One super fan cannot change the business choices of an electrical utility service.

• The household level

  • This level consists of items that are commonly purchased or discussed on the household level. The sales funnel might be in contact with different people at different stages. At this level, a more granular analysis could be infeasible or useless.

  • Examples: Cable subscriptions, house cleaning services, vehicle choices

  • A cable service should consider doing analysis by household level. It does not matter if the father likes HBO if everyone else isn’t interested.

• The individual level

  • This level consists of data resolution down to the natural person (normal human) level. At this level, a single person touches all stages of the sales funnel throughout the process. (Jekyll and Hyde would be indistinguishable at this level)

  • Examples: Clothing choices, toothpaste brands, book purchases, candy bars

  • A clothing company is concerned with the buying habits at the individual level. Trends at the macro stage can (and do) shift regularly, but understanding the shifts within your existing² customer base is more important than trying to copy general trends.

• The mood level

  • This level consists of very detailed resolution down to the state of mind for an individual. A person in a certain mood is the object of research at this stage. (Jekyll and Hyde would be separate here)

  • Examples: Alcohol ads, impulse candy purchases, hotels & resorts

  • No normal person would willingly pay $50 for a hamburger at a restaurant, but many people, when in the vacation mindset, are happy to order room service as a treat to themselves. It would be foolish for a hotel to advertise their room service menu as an alternative to a normal restaurant with patrons in a different mindset.

The levels of data resolution are like Russian nesting dolls.

Each level below is implicitly contained within the data above³ and lower level data can roll up (‘deresolve’) into the higher levels as needed for the analysis.

Levels of customer resolution as Russian Nesting Dolls

Benefits of Data Resolution

Resolving data across various platforms to the correct level of resolution will allow you to take advantage of many of the promised⁴ advances from the collection of good data.

A few

1. Enhanced Customer Insights:

   1. Data resolution allows you to create a unified customer profile by combining data points such as demographics, browsing behavior, purchase history, and engagement metrics. This comprehensive view enables better segmentation, personalized targeting at the correct level for your marketing strategy, and more effective customer relationship management.

2. Improved Decision-Making:

   1. With unified & resolved data, marketers can make data-driven decisions based on a complete and accurate understanding of their marketing strategy, performance, and customer behavior.

3. Seamless Cross-Channel Campaigns:

   1. By unifying data across different marketing channels, marketers can make sure they deliver the same message to the same customers across channels.

Data Resolution in Action

Examples from Industry Leaders

We’ve so far talked about data resolution in the abstract. Many SaaS companies (and open source) have data resolution tools or processes.⁵

I’ve described below a few common tools I’ve worked with.

In no way is this a comprehensive list, just a stepping stone to get you started in your search for the right tool.

1. Salesforce Marketing Cloud (SFMC)

   1. Salesforce Marketing Cloud, a leading customer relationship management (CRM) platform, offers data unification capabilities. By integrating data from various sources, such as email marketing, social media, and customer service interactions, you can gain a comprehensive view of their customers. Once you have a full view of all the data across collection channels, you can resolve it to the level appropriate for your strategy and track marketing performance

2. Adobe Experience Cloud (AEP)

   1. Adobe Experience Cloud provides a suite of tools that enable marketers to unify and analyze data from different touchpoints. With its Data Management Platform (DMP), Adobe enables you to consolidate data from online and offline sources, including website analytics, mobile apps, advertising platforms, and more. By unifying data, marketers can uncover valuable insights, segment audiences effectively, and optimize their marketing strategies for better results while ensuring that marketing strategy and business strategy align.

3. Tealium

   1. Tealium is a packaged Customer Data Platform (CDP) tool that allows you to define a unification ID and logic to ‘stitch’ together various channels of data into a single customer profile. This can be used to consolidate data from web behavior, ordering history, transaction logs, mobile apps, etc. By defining the unification logic for your business, you can ensure that you achieve the desired level of data granularity.

Conclusion

The gusher of consumer data without a control is a dangerous and expensive liability to have.

Knowing the impacts from correctly resolving data will bring you head and shoulders above the market.

As you grow in your understanding of customer data, make sure you align your marketing strategy to your business goals, collect and structure data correctly, and now, resolve it to the appropriate level.

1. Resolve in this context means something like:

• “to separate or cause to be separated into components” or

• “to turn into a different form when seen more clearly”

2. or adjacent

3. Although the more granular levels of data cannot be elucidated without further data collection / analysis

4. promised but often unrealized

5. If you’re looking to try this out without paying, there’s an open source Python library that you can customize to your level of granularity. Dedupeio