One day, we'll also invest in attribution. Crashing into growth marketing: a CEO journey. Part 5.
By: Johanna-Mai Riismaa
Tags: Growth Marketing, Zelos Team Managemen, Startup, Cxl Institute, Growth Hacking

What does it feel like?

The CXL course has been an integral part of my life for a month now. And will be for another two months. Yes, I’ve rescheduled most of my life to accommodate the amount of time that I need to spend on this.

While it doesn’t take ages to press play and watch the course videos, going through the classes does take up a fair amount of time from my daily calendar. The new concepts need time to digest — and I’ve found that this is best done just staring at my notes and out the window in the end of each video. Five minutes gone.

Many aspects don’t really become clear before I’ve tried them out in practice. Cue countless hours of staring at our analytics. Instant messages to my CTO and CMO. Stupid questions about our website, asking for access to stuff I didn’t have access to. Getting access to accounts I never knew we had.

And of course, I’ve spent a silly amount of time on my private project, the publishing house that promotes my husband’s novels. I’ve installed and configured an obvious overkill of analytics and content strategy to promote the Christmas special (two novels gift-wrapped), and we’re actually seeing a pretty nice volume of books bought each week. I’d love to think it’s because of my new and amazing “marketing efforts”, but in reality it’s probably because people are looking for pre-wrapped holiday gifts to purchase, and freshly printed books are a neutral present when you’re out of ideas.

I’m able to take these extensive hours off my calendar as we’re currently living through the second wave of COVID-19 pandemic of 2020, and while Estonia isn’t in official lockdown (yet), there’s not many places I’m going during my day to day, even during business hours. Maybe I’ll stand up to refill my coffee between Zoom calls. Maybe I won’t. Who knows, let’s see what radical surprises the new day may bring!

CXL is definitely not beginner material, and I appreciate it. All of the courses I’ve taken during this first month have done a long deep dive to the actual practicalities of the topics. So not only am I generally learning about what’s supposed to be happening when one plans and executes marketing activities, I’m acquiring the knowledge of how things are supposed to be happening and what are the bits and pieces of effort that actually need to be put in.

And so far, I totally don’t think it’s an overkill for a startup CEO to know these things. We have a B2B SaaS product, and the only way we’ll be actually successful is by getting our marketing right.

This is the fifth post of many to document my journey as early-stage startup CEO through the growth marketing minidegree by CXL Institute — a 12-week online program about the practicalities of growth marketing.

Disclaimers: I’ve done intense learning sprints before. I’ve never touched marketing from a practical perspective before this course. Consult a specialist before trying this at home.

Promo insert: My startup is called Zelos, it’s an app that helps you manage tasks and distribute activities with a very large group or community, and you can sign up here for free: getzelos.com

But let’s get to the point.

Notes: attribution is not about math, but people.

Is Excel a core survival skill?

I went to an art university, and nobody has ever taught me how to use excel sheets. I learned to mix audio on ProTools production software and program custom effects on Grand MA lighting boards — both extremely useful skills! But I was never introduced to spreadsheet formulas.

When I got into production and management jobs, I obviously had to start working with online documents, and most of them were spreadsheets. By now, I’ve worked with SO MANY spreadsheets, and I’ve created SO MANY spreadsheets, and I thought I was awesome at learning by doing. I really thought my spreadsheets were better than other people’s spreadsheets.

But my oh my, learning by doing isn’t the good answer here.

Anyways — CXL marketing course comes with a quick insert on Excel and Google Sheets, and it taught me quite a few things.

Do you really know, like know-know how to use pivot tables?

Are you getting the most out of named ranges?

Did you know about sparklines?

How have I been able to live without sparklines?

We are going to have sparklines in all spreadsheets from now on. OK maybe I’m a little too excited about sparklines. But we’ll definitely have better spreadsheets from now on.

Attribution

The main topic of the week has been attribution. Let’s be honest, I did not really know this was a marketing word before I started the course, and I had to google what it means.

In marketing, attribution, also known as multi-touch attribution, is the identification of a set of user actions that contribute in some manner to a desired outcome, and then the assignment of a value to each of these events.

So, from what I learned, attribution is the analysis that comes in handy when you have:

Lots of traffic (we don’t)

Lots of conversions (we don’t)

Lots of paid marketing activities (we don’t)

And you are trying to answer the question:

Which activities make your users convert? (We cannot tell for sure!)

Which activities should you invest in? (We’d love to know!)

While we’ll probably not be able to afford answering these questions with actual data, it’s great to learn how one should do it at the “pro level”. Attribution breaks it down to more questions:

Which of your things did the customer do before buying your thing?

In which order did they do the things?

How much time passed between doing those things and buying your stuff?

“Those things” are the results of your marketing activities here — any passive or active event where the customer gets influenced by your brand and products, like looking at your ads or reading your blog, clicking on stuff on your site, or attending your webinar.

Attribution tries to calculate the value of each customer (how much did they spend, how much is their contract worth, etc), and then allocate this value to the events (also called touch points) that led up to the conversion. Which touchpoint broke the camel’s back? Why did they buy your thing?

Was it the ad they saw on TV?

Was it your amazing homepage?

Was it your remarketing campaign?

Because you will totally want to:

create segments based on personas and their point in journey

target different activities for those really likely to convert right now

target different activities for those not likely to convert (yet)

figure out how to convert in less touch points

The bottom line answer is — it costs a lot of money, time and resources to find out. Sorry — not find out — come up with an informed guess.

It’s not about math, it’s about the people.

While it may sound attractive to just track and record a bunch of data on user activity, the course makes a really clear point — do NOT invest in attribution unless you are sure you have the skills and resources to actually use the data and change the way you run things based on the outcomes.

Appropriate attribution will let you make informed guesses about the probable outcomes of targeting a certain segment of your audience (the value of attribution is always in the aggregate, never with individuals). But it takes a lot of smarts to figure out the best attribution model, and make use of it. It’s not the easiest challenge to look at the users of today, and make predictions and decisions on how they’ll behave in the future. So the answer does not lie in just hooking up some AI to your analytics.

You need to decide on the correct granularity of your data, make sure your data streams are in the same format, and then get your data to a central location to achieve data integrity. It can be quite a challenge if you’re marketing on all channels — PPC, display, affiliate, email, TV and direct channels can be very very different in terms of what data is being produced.

But if you’re at the stage where attribution is becoming a relevant decision making tool (with tons of traffic and conversions), you’re probably marketing on quite a few channels.

So yeah, you need to have someone on the team who knows what they’re doing.

Attribution models

At the core of attribution is the model — what is the sense-making way of crediting the different attribution channels — how much should they be praised for bringing in converting customers. While some marketing activities target the beginning of the customer journey (focused on awareness) and others chime in near the end (focused on instant conversion), different models come into play.

Last non-direct click

This is commonly used in web analytics tools like Google Analytics and AdWords. If the client was referred by a channel less than 30 days before converting, this channel takes 100% credit. If there was some direct traffic after the referral, that does not count.

This is commonly used in web analytics tools like Google Analytics and AdWords. If the client was referred by a channel less than 30 days before converting, this channel takes 100% credit. If there was some direct traffic after the referral, that does not count. Last interaction

Whichever route the customer arrived that time they made their purchase, is their attribution channel and takes 100% credit.

Whichever route the customer arrived that time they made their purchase, is their attribution channel and takes 100% credit. Linear attribution

This model gives the same value to all visits, as if they all impacted the decision equally. If the client was referred through four different channels and ended up spending a hundred euros, each channel would be credited 25. Although sometimes in use, the wise men do not recommend this as a good attribution model.

This model gives the same value to all visits, as if they all impacted the decision equally. If the client was referred through four different channels and ended up spending a hundred euros, each channel would be credited 25. Although sometimes in use, the wise men do not recommend this as a good attribution model. Time decay

The values are distributed back from the last interaction, giving less and less of a share the further away the interactions are from conversion.

a) static time decay — gives fixed percentages to channels in order (i.e. 3% — 7% — 20% — 30% — 40% at conversion)

b) variable time decay — calculates percentages based on the time passed between the interactions

The values are distributed back from the last interaction, giving less and less of a share the further away the interactions are from conversion. a) static time decay — gives fixed percentages to channels in order (i.e. 3% — 7% — 20% — 30% — 40% at conversion) b) variable time decay — calculates percentages based on the time passed between the interactions Position based, or the “bathtub model”

This model gives most credit to the first interaction (awareness) and last interaction (conversion), while leaving a bit for the interactions in between. This aligns well with the actual human behaviour, where people put most emphasis on “the first time I learned about the brand” and “the time I actually purchased”.

This model gives most credit to the first interaction (awareness) and last interaction (conversion), while leaving a bit for the interactions in between. This aligns well with the actual human behaviour, where people put most emphasis on “the first time I learned about the brand” and “the time I actually purchased”. Machine learning

Ideally, the model should be run by machine learning, as the marketer shouldn’t get to decide what’s important. Usually this brings up the cost a lot, so it’s most likely that one of the basic models are used.

LTV strategy

One of the concepts that most struck a chord with me was lifetime value strategy. This is something we’d.. forgotten? Stopped consciously thinking about? Didn’t think to write on a wall?

Re-acquiring a customer is always much cheaper than making a fresh acquisition.

You may spend 100 euros in marketing to acquire a client that checks out a 100 euro purchase once, leaving you with no profits. But it’ll cost you 10 EUR to bring them back a second time, and it’s most likely that they’ll spend at least 110.

An early stage startup is always a leaky bucket, with a lot of churn and leaving customers. But we can still put more focus and effort on our existing leads, instead of only shovelling in new ones in hope that they’ll stick.