Reporter's Notebook: McKinsey's Heller Talks Analytics

Jason Heller, global lead for digital marketing operations at McKinsey & Co., shared his thoughts at the eMetrics Summit in New York last week on “How To Help The CMO Succeed.” Here are some highlights from his presentation to an audience of data scientists and statisticians about the role of analytics in supporting the CMO mission.

The mission of the modern CMO is closely aligned with that of the CEO — driving growth and value with responsibility for the entire customer journey.

CMOS are asking: Do we have enough data scientists? Are we accelerating customer acquisition? Are we increasing customer value?

What they care about is taking the intense amount of data that happens every day from call centers, Web sites and stores, then stitching it together and identifying new customer segmentation and new opportunities to create growth. The CMO is thinking about data science — how it can drive growth about the organization.

The biggest single value creation event for analytics is taking the walls down between fiefdoms to create a 360-ish view of customers — “unlocking derived insights.” 



The CMO needs help wrangling and activating data to create value. Media data, social data, transaction data, engagement data, call center data, third-party data. Enabling personalization of your own channels. It’s not the status quo today.

Where To Start?
If you wait to create a perfect scenario, you’re never going to get there. Figure out how to carve out the opportunities to create as much of an opportunity as you can. Take a 360ish view. Make yourself an agenda. How do you spend some portion of your time, even if it’s just influencing part of your organization to get involved with the discovery rather than the reporting.

The consulting companies — McKinsey, Deloitte, and others — are building the systems for a customer data platform because the industry doesn’t have one. A platform that creates scores on your customers.

The way a CMO looks at value is mining through the data, which has a whole world of output to it — everything from voice of the customer to third-party data — especially for CMOs of large organizations. I can have a meeting with a CMO who has a billion-dollar marketing budget and doesn’t know where any of that money is spent at any one time.

To be able to provide marketers the ability to see how our money and human resources are being allocated — that’s where CMOS want to be.

Building A Better Model
We are in a world today where we can addressably reach consumers at scale. We know anonymously through third-party DMP partnerships. We know their interests. We have all that data. As soon as somebody logs in or transacts, we can take all that data and link it to verifiable deterministic data.

If you’re tracking everything and combine with the data once someone transacts, if you’re not linking it together with all the anonymous data, the footprints they left, you’re missing the opportunity to create a rich look-alike model.

That is real segmentation. It’s where the customer’s worth the most to the organization and here’s an addressable way to find it. You can create a DMP. All the traffic can be personalized so your highest-value customer segments actually receive the offers most valuable to those segments.

One company McKinsey is working with will generate an additional $250 million in 2017 because a 10% increase of the conversion rate of their previously unidentified traffic is worth that. Report results in a way that means something to a CMO. A .2% conversion rate means absolutely nothing, but if you went from .1 to .2, that’s a 100% increase. And a 100% increase of a bad conversion rate is a lot of money.

The 4Ds
Here’s an organizational framework:

  • Data. Aggregate as much information as possible and everything you do downstream creates more value.
  • Decisioning. Run advanced models — propensity models, churn models — against that data. You don’t become a data scientist overnight. The organization needs to do customer scoring and advanced analytics. Identify where the data fiefdoms are in your organization (people holding on to their data to protect their jobs) and get the right people together.
  • Design. Managing the content, offers and experience the customer receives and being curious and experimenting. Testing. A/B testing. Once you have the models, what are the experiences these customers want to see?
  • Distribution. Push both the decision data and test design into marketing. Close the loop and measure everything. If I’m in a room of marketers and I ask them what their roles are, they’re distributing marketing communications, just not in a truly data-driven way.

Agile Marketing And The 5X Sales Increase
The new marketing operating model is the concept of agile marketing. It borrows from agile software development, allowing for true rapid iteration and value capture.

A banking client that would do one A/B test every month or two can now execute a test on Monday, launch, and in a week increase digital sales by 5X while working with some of the biggest digital agencies doing the job well. It wasn’t until it took the capability internal that it became good and fast — focused on analytics for both the discovery and reporting side. They put a team on it to act immediately. War rooms were set up. One of the most critical roles is a discovery analytics role.

5 Core Beliefs Behind Mobilization

  1. Mobilize cross-functional leaders around the opportunity. The CMO needs CIO, store operations, different people to help break down the silos.
  2. Get creative about navigating the legacy … be relentless about solutions.
  3. Walk before you run. Identify a roadmap, pick some high priority areas and execute.
  4. Prioritize “lighthouse” projects to kick-start execution.
  5. Let data activation drive your new marketing operations model.

Some Big Payoffs
We see real aggressive growth with clients doing nothing wrong in the range of a 6X revenue capture. If I can increase the speed by which you test, you’re increasing revenue .

Typically conversion rate increases from the low end of the 20s to high end of 150%+ range … on the digital sales side yield exponential gains of 2, 3, 5X. Just 1%, 2% or 3% of enterprise value creation for a multi-billion company — driven by digital — is huge

Correction: The timeline for a client doing an A/B test and increasing sales 5X has been changed from "in a week" to "in 6 to 12 months."

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