The adjective data–driven means that progress in an activity is compelled by data, rather than by intuition or personal experience. It is often labeled as business jargon for what scientists call evidence-based decision making.
compelled by data… yeah that’s not happen. There seems to be this uptick in people who think they are data driven and yet they can’t even understand some basic data points that are clearly labeled and given to them by someone.
If you think telling me average time on site is data drive, it’s not.
If you think telling me I feel this is right about campaign is data driven, it’s not.
If you think telling me your personal opinion is data driven, it’s not
If you can’t understand basic data points in a spreadsheet, you’re not data driven.
If you can’t pull anything from Google Analytics or MixPanel beyond the basics, you’re not data driven.
If you can’t create a compelling hypothesis from data given to you, you’re not data driven.
There are too many C and B marketers out there who think they have a mature marketing mind and are data driven. They are not. They need to recognize this and increase what they know about data, gathering information and understand what’s going on. It’s 2016.
A few day’s ago I was doing some indirect competitor research and came across a double listing for 99Designs. They served me a .com & .ca paid search ad…which is wasteful at best. Not sure who runs their paid search but that person or agency should be doing a better job.
However, it got me thinking about what if every brand started showing a .com and a local TLD for ever search results related to their brand name. With right hand side ads being extinct, this would be a smart strategy to gain more SERP real estate with the only down side being wasted impressions on one of your accounts.
This could be a mistake on 99Designs part but maybe this is a bold new strategy they are trying with the new reality of the search world we live in.
I’ve been documenting my attribution modelling journey….and as I often say; good is better than perfect. If you’re startup or a smaller brands looking to move beyond lack-touch attribution. Then this blog post series is for you.
This series looks over the last 8 months and the work I’ve been focused on more and more as I struggle and research what’s the best path forward. Like any marketing, this is an orgaism and it’s change and grow over time. Some things will get added and other will get cut away and that’s ok.
The key point is you’re looking beyond last touch and growing your business in the right way.
…as I try to figure out a model that works for startups. It’s not perfect, though it’s a starting point and good is certainly better than perfect so we can launch something and iterate as we go.
If you’re a startup and resources are scarce and you can’t get money to use an attribution vendor (yet), than we’re in the same boat and this post is for you. So today I want to share the framework I’ve started to work on and what shape it has taken. To build this framework I started by answering the 3 attribution questions in my last post.
Defining Success and our Attribution Window
Customer signing up for the service is our main KPI. However, I also look at people subscribing to the blog, downloading an ebook or whitepaper. The last two are tracked because maybe a campaign you thought would be for driving customer acquisition, is actually more suited for blog subscribers or getting people to download an ebook. If your company offered webinars or product demos and you’ve those as goals (or events) in Google Analytics, than you can add that to the spreadsheet below.
I picked a 30 day attribution window for the cookie that sits on a customer’s computer. However, when I think about the effect of a campaign and how long to look at it after it launches. I picked 90 days because we don’t generally have long sales cycles and if someone takes longer than 90 days to convert, it becomes a mess to track. If I had more time I’d look at 180 days after a campaign launches to see its effect on the business. Maybe that will be round two for next year.
The spreadsheet below is what I created when I put everything together. I added in a threshold of $500 for campaigns we track in this birds eye view because anything under that limit doesn’t tend to have enough data to make a proper informed decision that doesn’t risk getting a false positive for you campaign and data. All data is fake below and just to give you ideas of what your could look like.
As I wrote last month, I’m starting to think about attribution at work. I’m doing this because we’re trying to figure out how to judge the success of a campaign we launch. I’ve already written about the 5 different multi-channel attribution models and what makes each one different. As I’ve started down this journey though, I’ve came across one more model that’s interesting and promising: Last Non-Direct Click
This takes all your conversions that show up under “Direct” traffic in Google Analytics (GA) and looks at the second last click before that conversion happened and resigns it to that channel in GA. Many customers will come to your site through a campaign or a landing page and then bounce off your site and or look at other pages on your site. When that happens, those customers will then become a “Direct” channel customer because going from a sub-domain to your main site domain will cause them to get reclassified in Google Analytics.
Working in the performance marketing space for 8 of the last 10 years has been amazing. I’ve been able to use many tools and services to do my job better (and faster). Maintaining quality should always been […]