The era of the customer-centric business

Businesses have typically been built around understanding forces, groups, and trends. New technology is changing that paradigm by giving companies unprecedented visibility into the individual customer.

(Disclaimer: I’m not employed by Zodiac or affiliated financially with the company in any way. I’m just someone with a Data Science background who finds the company compelling.)

One of the most interesting shifts that technology has spurred over the past decade is the consumer-ization of enterprise. While the default software providers of a previous age (think: Microsoft, Oracle) were able to sell commoditized, poor-UX software through lock-in economics, things are changing quickly. The new age of software providers are customer focused. The Slacks of today actually care about their customer experience, and design their products accordingly.

While the increased transparency of social media and the internet as a whole have contributed to this consumer-enterprise spillover, one of the major drivers of this trend is the unprecedented visibility that modern businesses have into their individual customers. An emerging suite of tools can track individual customers across the product spectrum and drive personalized service and features.

A wave of web analytics companies led by Mixpanel and Co. give visibility into a customer’s website activity. Brandwatch enables analytics on your social media efforts. Pendo helps you grasp your customer journey and what you can do to improve it. It has never been easier to zoom in on what your individual customers are doing, and this is a major reason why enterprise products are getting easier to use and understand. But there’s still a large piece of the puzzle missing.

The wave of individual customer comprehension hasn’t spun out to CLV

There’s one area that this deep understanding of customers hasn’t extended to: the lifeblood of a business, revenue and profit. Comprehending what your customers are using your product for is important, but the ultimate end game is to guide your customers to continue paying for and increase usage of your product. What are your customers paying, and how much will they buy in the future? How much are they going to bring into the business going forward?

The metric at question is Customer Lifetime Value, often abbreviated as CLV or customer LTV. CLV is a measure of how much profit you forecast that an individual customer will bring in over their lifetime relationship with your business. Each one of your customers is going to act differently over time — some will drop off, some will maintain, and some will increase purchases––so every customer’s LTV will be different, even if ever so slightly. Understanding revenue and profit on an individual level, in the mold of the tools for engagement discussed above, should just mean understanding your CLV.

Unfortunately, that’s actually a pretty difficult problem: analyzing and forecasting sales is more of an art than a science. Over modern commercial history, things have shifted from looking to sales on an entire-business basis per quarter to a more granular view by department, but certainly not on a per customer basis. Businesses are fluid and grow and change over time. Customers are irrational and subject to a myriad of fluctuations. If we can barely guess what our sales will be next quarter, how are we supposed to know what individual customers will do?

What makes this problem even worse is how important it is — understanding your individual customers and CLV is absolutely key to running an efficient and impactful business. Especially if you’re a marketer:

  • If a customer has churned and won’t shop again: your marketing is wasted on him/her
  • If a customer is at risk of churning from the business: your normal materials aren’t going to be effective
  • If a customer has the potential to buy more: you’re missing an opportunity to up-sell

Marketing efforts need to be arranged around creating the most value from customers, and without an understanding of how much each one of your customers is going to buy over time that’s extremely tough. Being in the dark about your customer LTV means being in the dark about your customer.

Thankfully, new technology is bringing some light to the situation.

Zodiac and running a customer-centric business

Customer Centricity is about identifying your most valuable customers, finding more customers like them — and then doing everything in your power to make as much money from them as possible. — Peter Fader, Zodiac Co-Founder and Professor of Marketing at Wharton

Zodiac brings transparency to CLV in the same way that Mixpanel and Pendo bring transparency to the customer journey — by giving you a granular, reliable understanding of what your customers are spending and what they’re likely to spend in the future. Zodiac uses your past sales data and predicts how many purchases your customers will make, how frequently they’ll shop with you over time, and how much they’ll spend. It’s a full, 360-degree view of each one of your customers.

Simply put, Zodiac forecasts the cash each of your customers will generate for your business at each point in the future. This kind of understanding is absolutely key for marketers, because it allows you to differentiate between customers that are worth spending time and budget on from those who aren’t. For example: if Zodiac’s models predict that a customer is going to stop purchasing soon, that’s an opportunity for marketers to reach out and try to prevent churn. On the flip side, a high predicted CLV means that marketers can up-sell a customer and be relatively confident in success. Getting back to our examples before:

  • If a customer has churned and won’t shop again: don’t waste your time and budget on them
  • If a customer is at risk of churning from the business: target them with your retention materials
  • If a customer has the potential to buy more: up-sell and capitalize

Understanding your individual customers and CLV opens up a new line of transparency into how you sell and market.

How it all works under the hood

While there has been a lot of theoretical work done around understanding and predicting CLV, much has remained in the academic sphere. Zodiac’s models began with co-founder Peter Fader’s research on the topic at University of Pennsylvania, but their data science team has dramatically improved these models in proprietary fashion. While the publicly available models can have a forecast error of 30% over a 1 year horizon, Zodiac’s accuracy is typically within a 1–3% range on the microsegment level.

Models are built at the cohort level (i.e. a group or segment of customers), but predict unique customer action based on their actions relative to the cohort. For example: if a cohort of customers that you acquired 6 months ago typically spend around $200 per month but Justin is spending only $130, you can predict his individual future actions in relation to what the rest of the cohort will do.

A lot of the value that Zodiac brings is in connecting Professor Fader’s modeling and practical implementation — making them actually work for your business. Zodiac’s models are optimized to run at scale, while fully parallelized, and with extremely large datasets. No matter how big your company is or what kind of data you’re bringing to the table, Zodiac can get it up and running within weeks.

Data Science teams at major companies have been working on this problem for a while, but with mixed results. Zodiac’s different approach (Empirical Bayes and other Machine Learning techniques) and experience give significant improvements — farther out forecasting ability (2–5 years vs. 2 months) and higher forecasting accuracy. The company can also give predictions after just one purchase.

Why it matters

Zodiac’s tech enables a new way of running a business or department — Customer Centricity. If you know what your customers are going to do and who the most valuable ones will be over time, you can focus on extracting value out of the most likely places. Marketing and customer relationships don’t need to be cloudy and hard to navigate when we have the data we need to comprehend them.

In consonance with new tools that allow you to understand what your customers are doing and thinking, companies really can create new kinds of experiences that are customer centric. And I think that’s pretty cool.