T: @DuaneBrown

13 Tools To Help Market Your Startup In 2017

Startup Marketing Bullhorn

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 number 1.

I also believe in automation not repetition where possible. You should know how to do the task manually before automating anything (and why you’re doing it).

Below are some of the tools I use each week (some daily) to get my job done. A couple I’ve been using for 8 years now. They have stood the test of time.

Automation
Zapier – The software helps you connect two programs together that don’t have an official integration. e.g. importing a Twitter list into a Slack channel, so it’s searchable later by your team. I did this recently for a Twitter list I had based on research publications. Zapier’s recipe library.

IFTTT – It’s is a web-based service that allows users to create chains of simple conditional statements, called “recipes”, which are triggered based on changes to other web services such as Gmail, Dropbox, Instagram, and Craigslist. Seer Interactive put together a great list of IFTTT recipes for marketers.

AdWords Scripts – Provide a way to programmatically control your AdWords data. You can use scripts to automate common procedures or interact with external data in one to many AdWords accounts. A couple cool scripts I’ve been using over the last year are URL Link Checkers and Keyword Performance. Brainlabs also has an AdWords script library that is a great resource if you work in the commerce space or have a ton of different inventory and SKUs type clients.

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A Startup Marketing Framework: Attribution Modelling

I’ve been documenting my attribution modelling journey….

3 Questions To Ask Yourself About Multi-Channel Attribution
When Do You Use A Last Non-Direct Click Attribution Model?
The Journey To Multi-Channel Attribution
Multi-Channel Attribution That Goes Beyond Last Click

…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.

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When Do You Use A Last Non-Direct Click Attribution Model?

last_non_direct_click_attribution_chart1

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.

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The Journey To Multi-Channel Attribution

multi_channel_attribution

Attribution has been all the rage at the office the last few weeks. From looking at what would happen if we turned off paid completely, to how we can look at multi-channel attribution but not actually look at multi-channel attribution to judge the success of campaigns we’re working on. To judge the success of a campaign, beyond getting a customer, I’ve started to look at longer attribution windows and look at different goals within our organization.

I’m starting to only hit the tip of the iceberg and though my model is rough and could use a lot of work. It’s a starting point and you’ve to start somewhere…or you’ll never get anywhere.

The last few weeks have reminded me of a good post a few months back looking at 3 top UK retailers and how they have grown up and handled going from last click to multi-channel attribution. A line from the article I like is…

At the end of the day the data has to tell a story and it’s not always the story you want told but one that needs to be told.

How To Build a Custom Report In Google Analytics

Google Analytics Custom Report

Last months we talked about running paid search globally while staying a nimble team. Once you’ve launched a global account, you’re going to want to optimize & lower your CPA while growing your business.

One way I like to optimize a global adwords account is by building custom reports in Google Analytics. Custom reports can present different data sets and show:

  • Which country is driving the most conversions
  • What times of day are converting e.g dayparting opportunities
  • What days of the week are we losing market share
  • Month over month or year over year comparisons
  • Which products are selling / country

These are just some of the options when building a custom report in Google Analytics. Anytime I’ve said I wish I could see X or slice data by a third or fourth dimension in Google Analytics, custom reports has saved the day. This is especially true if you’re not a fan of pivot tables or don’t want to download thousands of rows of data.

We’re going to take a look at the first option on my list above; which country is driving the most conversions. It’s a basic report but a key one since we can’t easily get that data in AdWords. I deliberately chose not to add each country, outside our top markets, in our global adwords account as I wanted to save time and I wasn’t sure what countries would perform well. Below is what the standard custom report would look like.

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