Category: Data/Analytics

Analytics Advice

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Episode 101: Age of Customer Equity, with Allison Hartsoe

Think of the data you have on your customers as having value. It does, by the fact that the more you know your clients, the better you can serve them. This “unlocked potential revenue” of all your current customers can be quantified as your whole customer’s lifetime value (CLV) added together. 

This number is known by finance people as Customer Equity, but it’s much more than a mathematical formula. The value that VCs and public markets have put on assets such as loyalty programs and subscription lists is often greater than the value of a company’s capital assets!

While it might sound like it has to do with finance, this is all highly related to marketing. This is because each tactical decision gets vetted by whether it will optimize CLV; it becomes your company’s North Star.  

Allison Hartsoe has strategize d the digital customer analytics for dozens of Fortune 500 customers throughout her career. She now leads an analytics consultancy in Portland OR, Ambition Data, and published the book, “The Age of Customer Equity”,  in 2021. She has been published in Forbes.com, MIT Technology Review, and Fast Company and somewhere in between all this writing, she found time to cycle across the USA. 

People/Products/Concepts Mentioned in Show

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Episode 99: Tying Revenue back to Traffic, with Steffen Hedenbrandt

Disclaimer: When I bring technology vendors on the show, you should know that they are not sponsors or affiliates. They’re simply here to give you a broader perspective.

If you have been to the eye doctor for near or far sightedness, the equipment that’s likely been used to assess you is a phoropter. The part that’s put in front of your eyes looks somewhat like a pair of glasses, but it branches out from that with an imposing array of lenses, dials and machinery. You are shown an eye chart and the doctor flicks through alternate lenses, asking you to say whether the image is clearer with lens 1 or lens 2. When tests on the phoropter & other equipment is done, you end up with lens prescriptions that are right for you. 

This process isn’t unlike what’s behind marketing’s use of attribution models. They serve to show what impact advertising channels have on a company’s revenue, with pre-set models, each one weighing the impact of digital touchpoints differently. By attributing revenue back to the channels and campaigns that helped acquire it, you get a clearer view of what you are getting for your marketing dollar. 

Of course, marketers don’t use phoropters, but doing attribution analysis does take specific tools, and that’s what this episode takes us through. 

My guest is Steffen Hedenbrandt, who’s growth-oriented, data-driven and loves all parts of scaling a business.  He worked at places like Upwork and Airtame before cofounding DreamData, where he serves as the Chief Marketing Officer.He has a bachelor’s degree from Aalborg University and a Masters from Copenhagen Business School. 

People/Products/Concepts Mentioned in Show

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Episode 93: Visualizing & Making Data Valuable, with Eric Boissonneault

In its raw form, data’s not worth much. If refined and put together with other data, it can be worth a lot. Here are well-known brands that built their value by creating a useful visual experience out of user-generated data:

  • Notable Examples:
    • Glassdoor
    • Nest
    • Zapier
    • Mint
    • Robinhood
    • Flipboard
    • Ancestry
    • GoodReads

This episode’s guest will help us see what is possible once you have data in your hands. Eric Boissonneault grew up loving numbers, but it wasn’t until he saw a Hollywood movie about card players at age 16, that he knew how he would apply his skill. He taught himself poker and methodically played this ‘game of chance’ so well that He became a professional player through his years at University du Quebec à Montreal and beyond. 

After cashing his poker chips in, he wanted to show the business world how they could look at the data they have on-hand as the basis for decisions. In 2020 he founded data consulting company Systematik to help businesses untangle, collect, visualize and understand their data.

Listen in this episode for Eric’s explanation of how you can put a unique transformation or twist on the data you already have, and even make an application that monetizes the data. 

People/Products/Concepts Mentioned in Show

How fast will you hit Google Sheets 5-million cell limit? If you have a spreadsheet with 5 tabs and each tab fills columns A to CW, and there is 10000 rows of data in each tab. It happens faster than you think.

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Episode 83: Quantifying Your Marketing Funnel’s Revenue with Keith Perhac

Disclaimer: The company featured here is not a sponsor of the show, nor have I affiliated with them. They simply bring a perspective that I think you’ll get some use from.

“It’s not working.” That’s the gist of every complaint made about marketing funnels. Marketers painstakingly build a series of offers and pay for traffic to see them, but the conversion rates drop off somewhere between there and the point where sales close.

Can funnels be fixed? Absolutely, but not without knowing a critical piece of data. Getting that data that helps fix the suboptimal parts of the funnel is our focus today. 

To go through this I’m joined by Keith Perhac, a digital marketing expert and software entrepreneur. After growing up in the states, he headed to Japan to become what’s known there as a salaryman. He moved back In 2010 to work with startups and digital marketers looking to grow quickly. He founded SegMetrics, a tool that lets you see revenue from the perspective of each touchpoint in your marketing funnel. Since then, he’s appeared on over 35 podcasts & in 2020 published the book we’re here to discuss, “Building Marketing Funnels that Convert, a 90 minute guide”

When he’s not working on SegMetrics, Keith draws and attempts (futilely) to spend more time outdoors. He lives in Portland, Oregon with his wife and two daughters.

People/Products/Concepts Mentioned in Show

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Episode 77: Stop arguing over leads; start scoring them, with Gary Amaral

Disclaimer: The company featured here is not a sponsor of the show, nor have I affiliated with them. They simply bring a perspective that I think you’ll get some use from.

Two things are required to get a clear view of revenue growth. First, sales and marketing must come together to jointly-define the thresholds at each stage of a lead’s lifecycle. Second, they must apply points to a lead’s every action, either manually or by layering automation on this process. 

My guest believes that lead scoring systems not only bring pipeline visibility, they improve the collaboration between Sales & Marketing. In fact, he claims that by pooling their information on leads and letting AI find the patterns, they can tell when a lead is ready to buy, upsell, or churn. 

Gary Amaral held several positions at places like at BlackBerry & Hootsuite, always at the intersection of marketing and sales. Seeing how poor scoring led to frustration for all involved, he joined forces with two other serial startup entrepreneurs. 

In 2020 they co-founded Breadcrumbs, which is a revenue acceleration platform based on a co-dynamic lead scoring and routing engine. Listen for Gary’s advice on what you need to do to get scoring right. Just as good communication helps keep couples together, the Sales & marketing relationship needs good communication on the status of leads. Lead scoring could very well be the glue in this marriage. 

People/Products/Concepts Mentioned in Show

You can also check out these episodes involving lead scoring:

Episode Reboot.

Download Breadcrumb.io’s lead scoring template

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Episode 61: Tools for wrangling marketing data, with JD Prater

Disclaimer: The company featured here is not a sponsor of the show, nor have I affiliated with them. They simply bring a perspective that I think you’ll get some use from.

What needs to be done with marketing data to make it usable?

Essentially, it must be taken from its original source, formatted cleanly, and put into your database to be analyzed. This is handled by a process called ETL, Extract, Transform & Load. This process was done manually in olden days, but AI is now facilitating this task to be almost entirely done by technology. 

Our guest can help us get familiar with how this works because he approaches it more from a marketer’s perspective than a technical one. JD Prater has a background in the world of paid media marketing, probably the niche that’s most famous for doing detailed analysis on large amounts of data. He has recently become Marketing Lead at Osmos, the maker of a tool that uses AI to help companies with ETL work. Besides that, JD has done marketing in-house at Amazon and Quora, and worked on brands while with a PPC agency. Besides that, he’s well known for speaking on digital marketing and being involved with several podcasts, and when he’s not on dad duty, you’ll catch him somewhere in his home state of Oklahoma, out cycling on an open stretch of road.

People/Products/Concepts Mentioned in Show

Episode Reboot

Go take a product demo of some tool you might use.

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Episode 53: Digital Marketing in an AI World with Fred Vallaeys – Summer Books

Disclaimer: The company featured here is not a sponsor of the show, nor have I affiliated with them. They simply bring a perspective that I think you’ll get some use from.

Chess Grandmaster Garry Kasparov was famously beaten in 1997 by a supercomputer built by dozens of IBM technologists. A Slate article looking at how Deep Blue changed chess said “The change here wasn’t just that a computer could win, but that a computer could help human players win if incorporated into their training regimes effectively.”

The same thing is happening with PPC Platforms. Since 2011, Google has been integrating AI into many of their products, and every campaign feature Google Ads rolls out seems to take away control from us humans and give it to their machines. So if we’re going to follow Kasparov’ lead and get better at this game with the AI, the question becomes, what’s the process for training an ad platform’s AI, when it’s writing programming that only it knows, and even the technologists running it don’t know?

Some answers are contained in the book Digital Marketing in an AI World. Fred Vallaeys was one of the first 500 employees at Google where he spent 10 years building AdWords and teaching advertisers how to get the most out of it as Google’s AdWords Evangelist. Today he serves as Co-Founding CEO of Optmyzr, a PPC management software system. Fred is a fixture on the marketing conference circuit and blazed new trails with online industry learning through Optmyz’s PPC Town Halls. 

People/Products/Concepts Mentioned in Show

Episode Reboot: 

Remember, computers have a different kind of smarts than us.

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Episode 51: The AI Marketing Canvas with Raj Venkatesan – Summer Books

Are you looking at how your marketing can use AI? That’s good if you are, but it’s not enough to know how it works. Whether you are embedded in marketing operations or you’re an executive who oversees it, you must also figure out how to get your organization to buy into AI. You’ll need stakeholders who own precious data, you’ll need knowledge experts to train your models, you’ll possibly need operations folks to change what they deliver…as AI informs what you offer. Lastly, you’ll need money – getting that money will take you proving that investing in AI yields a positive ROI. So by now, you’re probably wondering how you can implement AI. Well, if you are, you will definitely be interested in the framework called the “The AI Marketing Canvas”

It’s all detailed in a book by the same name, co-authored by Raj Venkatesan, along with Jim Lecinski.

Professor Venkatesan is a professor at the Darden School of Business at U of Virginia. He is also a co-author of the book Cutting Edge Marketing Analytics. Before coming to Darden, Venkatesan taught graduate students at the University of Connecticut. There, he was the recipient of the MBA Teacher of the Year Award. He received his Ph.D. in marketing from the University of Houston and his B.E. in computer engineering from the University of Madras. He has consulted with firms in the technology, retailing, media, industrial goods and pharmaceutical industries. 

People/Products/Concepts Mentioned in Show

Framework’s 5 stages, reproduced with permission:

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Episode 41: How Google Analytics 4 Impacts Marketers with Jim Cain

In fall 2020, Google released version 4 of their Google Analytics tool (here is the official announcement of GA4). Despite its description as a new version, this is actually a brand new product. In fact, it’s part of Google’s switch to a whole new technology stack, and the ripples of their move extend to the remotest corners of a marketer’s world.

What do you need to know about GA4? For one, it has a different interface from the existing “Universal” version of GA. It doesn’t have some features and functions that you assume are in GA. At the same time, there are things that GA4 has that you haven’t been able to get before without paying for GA Premium. 

My guide for this tour of GA4 is Jim Cain, who founded the analytics consultancy Napkyn in 2009, one of only a few Premier Google Marketing Platform Solution Partners. If you want to know what to do about GA4, Jim will tell you how Napkyn is dealing with it in their client work.

People, products and Concepts mentioned on the show:

Episode Reboot

Set up a GA4 Property onto your existing GA account as soon as possible, to run it in parallel with GA3.