Two Key Segments in Analytics Services

In the world of outsourced analytics services, two service models can be identified: the factory model and the boutique model. Players within these two models are very different from each other in important ways, so it’s helpful to describe the differences . . . and where Cartesian fits in.

Firstly, boutique does not necessarily equate to “small.” Cartesian, for example, participates in the boutique segment, and yet has 200 data scientists doing analytics work for more than 70 global brands. We perform more than 1,000 analytical queries per month, and manage 500 million records related to 160 million customers. That’s not a trivial resource! That said, services providers who compete within the factory segment, may have more than a thousand employees.

So, What is Boutique?

The boutique concept probably derives from investment banking, where the term is very well understood. The defining characteristic of boutique firms, whether in investment banking or in analytics, is specialization in at least one aspect of the broader category. Boutique investment banking firms such as The Blackstone Group, Brown Brothers Harriman, and Piper Jaffray have been steadily gaining market share. Whether in banking or in analytics, the value proposition of boutique stems from specialization and domain expertise. In the case of Cartesian, for example, although we don’t have thousands of employees, we actually have more data scientists devoted to customer analytics than the largest player in the factory segment. This is due to our focus on that area. So, which is better? a boutique firm or a BPO-style math factory?

Well, this is kind of like asking, which is better: a sports car or a pickup truck? The real question is: Which is better for you? These two models both exist in the market because they each serve a purpose, but they’re optimized for different things. Let’s compare.

Data Factory Model : Boutique Model :
Generalist. Works on a broad array of projects and for a broad array of clients Specialist. Focused on a few niches. Emphasis on synthesis of analytics and domain expertise.
VC Financing. Lots of pressure to ramp up client numbers, and to add client logos. Steady organic growth funded by profitable operations.
Strong focus on low – cost. High planned attrition (at least 20%). Lots of “newbies” Strong focus on employee retention. Much higher average tenure.
Typical projects are campaign list pulls and campaign response, or simple models, such as propensity or next-best offers. More emphasis on advanced models and problem definition-driven work (optimization problems, predictive analytics, future value, machine learning, custom models)
Emphasis on repeatable methods Emphasis on experimentation, exploring new techniques, higher-order methods.
Business development uses the “hunter” model. Clear hand off to an operations team. Business development uses the “farmer” model. Stays fully integrated within the end-to-end service delivery effort.
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