One and (Not) Done: The Takeaways


If you haven’t yet had the time to read our book (which you definitely should if you’re interested in customer analytics, shark graphs, and Paul Rudd), here are the top takeaways.

  1. The land-grabbing, Wild West days are over: the dominance of Amazon and ever-increasing choice are making acquisition more and more expensive and eating away at retailers’ margins.
  2. The key to improving margins is getting one-time buyers to come back. Study upon study reveals how critical repeat buyers are to long term growth. One stat says that increasing retention by 5x can increase profits by 125x.
  3. There are six critical capabilities to put in place before retailers can improve one-time buyer conversion rates:
    1. Data Consolidation: Creates a clean, single view of each customer from disparate data sources like online and offline purchases, web browsing, and email engagement.
    2. Predictive Insights: Machine learning and predictive analytics combine to anticipate customer behavior across channels, from product affinities to lifetime value.
    3. Prescriptive Insights: Predictive customer insights are curated down into meaningful recommendations and channel-specific actions to optimize opportunities for growth.
    4. Data Accessibility: An easy to use, point-and-click interface that empowers the entire marketing team to research and create audience segments without filing tickets to a centralized team.
    5. Channel Integration: Seamless integration with every marketing execution tool, from email to social advertising, eliminating the friction in campaign delivery.
    6. Customer Measurement: Incremental revenue and profit per customer can be measured with testing tools that cut across channels and monitor segment and sub-segment performance.
  4. Once these capabilities are in place, there are 5 steps to addressing the one-time buyer problem:
    1. Set Goals: Before any team can build a plan, it needs to benchmark and establish short- and long-term KPIs.
    2. Segment using quantitative approaches such as k-means clustering. The old method of “qualitative-first” segmentation is not rigorous enough.
    3. Build journeys and triggers for each segment. As a general rule of thumb, consider two “welcome” touch points per week. If possible, consider building a total of 12 to 16 creatives per series to last the first two months.
    4. Deploy across channels that will resonate best. Use email engagement modeling to learn who should be reached on which channels. Be sure to keep segments up to date.
    5. Measure and optimize: Use A/B testing and systematically use hold-out groups to measure incremental, multi-channel impact of programs.

Piece o’ cake.

Custora’s Q3 2016 Pulse Report

Every quarter, we release a report recapping the state of US e-commerce based on data from over 500 million anonymized shoppers and $100B in e-commerce revenue from over 200 online retailers. Check out this report to learn more about the top e-commerce trends of Q3 2016. For real-time updates, sign up for the Pulse here.

If you have any questions or comments regarding the report or this data, we’d love to hear them. Feel free to comment here, or email us at

If you’re curious about the statistical methods we used to produce this report, check out this blog post about a previous report, which used similar tools.

Please enter your details below to get the report.

One and (Not) Done



One time buyers. One-and-dones. One buy stands. Buy-bye bennys.

No matter what you call them, if you work in the retail industry, they’re a real concern. The unfortunate reality is the vast majority of customers who make a first purchase just never return. By simply patching the problem with a generic welcome series, you’re leaving money on the table. Our research shows that a 1% increase in customer retention leads to a 5% increase in profit per customer.

With the holidays (and the notoriously flaky shoppers that come along with them) approaching, you need a plan in place to convert more of those one-time Terrys into loyal Lucys.

To help, we wrote a book.

Weighing in at 100+ pages, this thing is the real deal. Granted, the font is big and there are numerous illustrations and obscure non-sequiturs, but it’s also chock full of insights collected across 5+ years of experience helping some of the world’s best brands build effective one-time-buyer programs.

It’s called, One and (Not) Done: Leveraging Customer Analytics to Address the One-Time Buyer Problem, and you can download it by filling out the form below.


The Six Steps to Activating Customer-Centric Insights in a Channel-Centric World

screen-shot-2016-09-07-at-2-54-02-pmMost retailers have made major investments in their marketing tools, their data, and their teams. They are aggregating customer information in data warehouses and making it accessible to marketing execution systems. New data science groups are being formed, and CRM teams are being integrated within the broader organization. So why is it still so hard to solve customer centric-challenges like the one time buyer problem? To reduce churn without over-spending on promotions? To focus your ad spend on consumers predicted to become high life time value customers?

In many ways, the last ten years have been the Age of the Channel. Email, Display, Search, Social, eCommerce -, the list goes on and on. Each channel has a dedicated team, dedicated tools, and dedicated analytic systems. But according to Forrester, we are now entering the Age of the Customer. And that requires customer-centric tools, customer-centric data, and customer-centric analytics that cut across channels. With all the investment in teams, data and technology, there is still a huge void right in the middle of the modern marketing technology stack that makes it nearly impossible to understand individual customer needs and wants. Without this deep understanding, brands will not be able to tackle customer-centric challenges like the one time buyer problem. Or reduce churn without overspending on promotions. Or efficiently acquire new high value customers.

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The gap in the retail marketing technology stack sits between customer data and the marketing teams themselves. Even after consolidating customer data in data warehouses, marketers still aren’t any better equipped to tackle difficult customer-centric challenges.  The gap is felt in two ways – through a lack of actionable insights generated from the data, and in the inability for marketers to easily access the insights to improve the day-to -day performance of the marketing team.

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Three Steps to Better Customer Insights with Guest Speaker Brandon Purcell of Forrester

Just as the 1960s were called the age of distribution, and the 1990s labeled the age of information, the 2010s have been dubbed “the age of the customer.” In this age, companies are reinventing themselves to better understand and serve customers who are becoming increasingly powerful.

As a side effect of the age of the customer, companies have been gathering massive amounts of data. While this data can take many forms (e.g. social, behavioral, mobile, sensor) and can differ from company to company, most of this new data has at least one thing in common: it’s not being used.

We work with smart people at some of the best companies in the world every day to tackle this challenge, but we can never pass on an opportunity to open the conversation to others. In that vein, we invited customer insights expert, Brandon Purcell from Forrester, to be a guest presenter at our webinar on the use of analytics to better leverage customer data.

We covered a wide range of topics with Brandon from fancy french restaurants, to Star Wars, and even Google Glass, but the biggest takeaway was these three steps to start using your customer data more effectively. (you can watch the full conversation below)
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