Lessons Learned from Building a Growth Team

Let’s start with a quote from Gary Vaynerchuk. There is a disproportionate value in being the first mover into a new space.

Those who adopt a platform or a marketing tactic first have a point of leverage over their competitors. This means they have something unique that makes it really difficult for their competitors to outgrow or surpass them.

Examples

HubSpot and Content Marketing
Moz and SEO/Content Marketing
? ?

When it comes to marketing and marketing tactics, it absolutely pays to be a fast follower. A fast follower means you’re not necessarily the first person to adopt that platform or tactic, but you’re in the leading pack of people who use it before it becomes really popular.

Let’s look at some examples

We moved ads online in 1994 in the form of banner ads.

This is one of the very first banner ads run on hot-wireds magazine in 1994. It was for a campaign run by AT&T.

It had a click through rate of 44%. Could you imagine how great our lifes would be if we could get a 44% click through rate on banner ads. Those early adopters must of thought they had found a gold mine.

There is a 2444% better click through rate on the banner ad placement on the HotWired magazine.

https://www.quora.com/What-is-the-average-CTR-on-Facebook-ads

Gary Vaynerchuck who’s quote we read earlier took over this dads wine business in 1996. It was generating near $3 million in revenue each year.

Gary turned this into 50 million by 2005. He did this by turning the wine store into an online ecommerce store and building an email list.

He had a weekly newsletter that he sent out to that list with wine recommendations

Those emails would often get open rates of 80%.

80% open rates !! I’ll just pause to let that sink him.

Over the years email has become a core component of a marketers toolset. It’s still an effective strategy but the open rates are in a state of continuous decline.

As we heard from Samuel Johnson earlier – “Whatever is common is despised”

People’s attitude to email has changed a lot the more it has been misused by both marketing and sales.

AirBnb, who are a private company with a market cap of over 20 billion dollars, used Craiglist in their early days to help scale the business. They created an integration with Craiglist, not an official one, they actually hacked one together that Craigslist eventually stopped, but it was to automatically post your AirBnb listing to their site.

This really helped AirBnb get some initial traction.

The funny thing is, Craigslist growth has been flat because it’s now being disrupted by those very same vertical markets, like AirBnB and Uber.

This is actually a common cycle in the world of marketing

Consider even a simple trend like the growth in popularity of the pop up. An influential blogger like Neil Patel will post results his had from implementing a Yes/No popup. He will talk about how much it’s helped him to increase his subscriber rate.

Fast followers are first to try it out for themselves, and more importantly, iterate and improve upon the original approach.

As more and more people blog about their results, theirs mass adoption, tools to help you automate the process. Once that happens, there is really only a downward trend where results will start to normalize for everyone.

Your goal is to be on this side of the curve. By being on this side of the curve you could of built up a substantial email list by the time results normalize give you an unfair advantage or point of leverage over your competitors.

Andrew Chen has the perfect quote to summarize this kind of trend

“It works for a while, until your customers get used to the effect, and start ignoring it”.

So there is an inherent advantage in being a fast follower when it comes to both platforms and marketing tactics.

Having a growth team or a growth culture within your marketing team helps foster a culture of validated learning’s, so instead of basing your marketing initiatives on assumptions, you actually base it on things you’ve tested and learnt from.

Think how more effective you marketing would be if you only did things that you’ve proved to be successful.

They can help you find points of leverage. Points of leverage make it really hard for your competitors to outgrow you. One of HubSpot’s points of leverage is the huge readership we have of our blog. We did this by being a fast follower into the content space.

And lastly a growth team will look to innovate on existing channels.

Here are some of the things we’ve learnt from running this model over the past 3 months.

We have a very experiment driven approach to growth.

I’ve segmented our learning’s on experiments into 3 categories.

The Goal of the Experiment
The Approach to the Experiment
The different types of Experiment

Let’s start with the goal for experiments.

Marketing experiments may not seem like a life changing event, but they can truly make a pretty big impact on the world.

The digital marketing team that worked for Obama’s election campaign was pretty remarkable. They saw everyone who visited their campaign website as an opportunity.

They decided to test two simple things, the splash page, so this Media part, and the call to action, so this giant red button here.

They tested 4 different media creative and 6 different buttons against each other, so that’s a total of 24 different variations.

This was the winning combination.

The media creative is really family orientated.

The CTA button has “Learn More”.

This variation increased sign ups by 40.6%.

Prior to the test the campaign team assumed adding a video as the creative would perform best. This is the advantage of running a model based on validated learnings.

Those additional sign ups added an extra $60 million dollars in campaign funds to Obama’s campaign.

Obama’s digital team continued to run dozens of experiments across the website to increase the number of people who donated funds, eventually helping him to be elected president of the United States.

The best growth marketers are very good at focusing and obsessing on a singular goal.

To do that you need to:

Knowing and prioritizing those metrics will change how you measure the success or failure of your experiments.

Our blogs are a really important part of our business. They produce millions of visits per month and thousands of leads.

The reason they’re so valuable as a source of leads is we spend a lot of time running experiments both across the content we produce and how people can convert into a lead.

This is Pam who is also on the growth team, feel free to tweet her and say hello from theinbounder.

Here is a perfect example. One of the teams I run is the growth of our sales products. One of those products is a free CRM. We ran a split test on our main sign up page where one page just had a “Get Started” button and the other included both the “Get Started” button and a video case study about the product.

That video is just in a pop up if you click on that link.

Talk about the learning:

Curios people will watch video instead of signing up
Others who may of went into the tool and gave up, after watching the video, will know how the tool can benefit them and be more committed to use the tool

The original version of the landing page generated 30% more sign ups over version B.

So video wasn’t great for getting people to sign up.

But version B actually generated 10% more active users, people who didn’t just signed up, but actually used the product on a weekly basis.

If you’re trying to grow an audience for a freemium product, than having people actually use the product is a lot more valuable than sign ups.

If we had only measured on sign ups, we would of selected version A.

This is the value of knowing that singular goal and metric you want to obsess over.

You want to make sure those learning’s are being shared across the team. We took same experiment and ran it across another of the products that I’m responsible for – LeadIn.

Our blogs are a really important part of our business. They produce millions of visits per month and thousands of leads.

The reason they’re so valuable as a source of leads is we spend a lot of time running experiments both across the content we produce and how people can convert into a lead.

This is Pam who is also on the growth team, feel free to tweet her and say hello from theinbounder.

Ben, who is a growth marketer for LeadIn, ran a very similar experiment, with one landing page including a video and the other didn’t

This time the page with the video actually generated 13% more sign ups than the original

But it actually increased active users by 130%

Our learning’s from these experiments was that, when there isn’t a video available, curios users would just sign up to the product because both of them were free. But learning about the product by just signing up may not of been the best path for them so they didn’t become active users.

When a video was added, it provided a lot more context on the product, so a lot of curious users, in the CRM’s case, didn’t sign up as it wasn’t a fit for them, but those who did, had a better understanding of the product value so become active at a higher rate.

Running this kind of experiment driven model to marketing requires you to have a model that helps you focus on the right experiments.

We use something called the PIE model to make sure we’re only working on those experiments with potential to make a real business impact.

Explain

Ok, so you’ve understood how to set the right goals for your experiments, figure out the right metrics to track and use the PIE model to stack rank these in order of importance for the business.

Ok so you figured out that a team focused on growth obsesses over a single goal, they know the metrics and which ones to judge the success or failure of their experiment by.

You’ve got a model like PIE to stack those experiments in order of those that will benefit you most.

Let’s talk a little bit on our approach to experiments.

Each marketer on the growth team has their own experiment funnel.

We manage this all through Trello.

This is what one of our growth marketers experiment funnels look like. Like a typical marketing funnel it’s wider at the top.

You’re always going to have more ideas for experiments than actual experiments you’ve executed on.

You evaluate those ideas to identify if they’re worth your time. You need to get enough information to allocate it a PIE score, so you need to know the potential impact of the experiment on the metric or metrics you care about. You need to know the importance of the experiment to your business, does it influence the one metric your business really cares about.

And how easy is that experiment to implement.

During the evaluation stage a lot of experiments may get killed as they’re considered not worth doing.

Those you want to move alone are PIE scored, stack ranked and then added to running in order of priority.

In the Analysis stage you’re identifying the results of that experiment

And the outcome is where you document the actual outcome of the experiment and describe what you’ll do with the learnings from that experiment.

We have a shared experiment board where all experiments that are planned, running, in analysis and have documented outcomes can be filtered in a bunch of ways.

This really fosters a culture of shared learning where all team members running this growth playbook can learn from each other.

In any given week we have 30 to 30 experiments running and having a shared board allows us to provide feedback across each others experiments and also get an idea of what other people are working on.

Remember, like any good poker player, most growth marketers only share their wins. But for every win, there are probably 5 experiments that either failed or were inconclusive.

The goal isn’t to have 100% success rate on your experiments, the goal is to great a model where you validate assumptions and find those couple of things that will help you make a real impact on the metrics you care about.

Ok, so the final part of this is the type of experiments you can run. The following are the categories we assign experiments to, they may differ from those you’ll want to run.

The first category is probably one that people don’t associate with an experiment, that’s analysis.

Our blogs are a really important part of our business. They produce millions of visits per month and thousands of leads.

The reason they’re so valuable as a source of leads is we spend a lot of time running experiments both across the content we produce and how people can convert into a lead.

This is Pam who is also on the growth team, feel free to tweet her and say hello from theinbounder.

The search query you’re trying to rank in the answer box for should appear in the header, usually as a h1, h2 or h3.

Directly after this you have clear steps that answers that query.

This one is pretty straight forward, in general the answers were between 54 to 58 words.

Our blogs are a really important part of our business. They produce millions of visits per month and thousands of leads.

The reason they’re so valuable as a source of leads is we spend a lot of time running experiments both across the content we produce and how people can convert into a lead.

This is Pam who is also on the growth team, feel free to tweet her and say hello from theinbounder.

When segmenting our content by word count, it became obvious our most successful content was longer form content. The reason it gets more organic traffic than any other kind of content is because.

It attracts more inbound links and social shares. People are more likely to link to that content and share that content.

This kind of analysis can help us run experiments around the right mix of content formats and lengths. We’ve ran 6 month experiments before across the content mix on our blog to get this mix right.

Across our blog posts we have these image links at the bottom of each one to generate a lead. They’ve historically been a great source of leads from all of our blog traffic.

We track the conversation rate of all CTA’s across our blog. This means we can spot when the conversion rate of CTA’s start to decline and it allows us to spot opportunities to run some tests.

We wanted to test against call to actions that looked less like Ads.

So we took 11 posts and tested the end of post image CTA against a more natural looking CTA that looks like it’s part of the blog post itself. These increased the number of leads per blog post by 121%.

In some cases we found these CTA’s converted between 5% and 6% where as the end of banner CTA’s converted at about 1 to 1.5%

We track the conversation rate of all CTA’s across our blog. This means we can spot when the conversion rate of CTA’s start to decline and it allows us to spot opportunities to run some tests.

So, once we had that result, we thought, would doing a small redesign of our blog help increase the click through rate of those call to actions even further

We originally had this sidebar that surfaced up additional content. It was really optimised for content discovery.

The experiments you add to this category are about finding points of leverage over competitors. These are the examples I mentioned earlier where you get an unfair advantage, they help you grow quicker and build a moat around your business.

Running experiments as pilots means you’re testing something new. No A/B or multivariate test exists because there is no original to test against.

The experiments you add to this category are about finding points of leverage over competitors. These are the examples I mentioned earlier where you get an unfair advantage, they help you grow quicker and build a moat around your business.

Remember this chart showing the decline in email? Well experiments under the pilot category can help your marketing take account of future trends vs just optimising for current ones, or worse still, historical.

We’ve started to invest time in building out a slack community for our different inbound channels, marketing and sales.

In 2 or 3 years time, having a really big slack channel could be a real point of leverage as email continues it’s decline.

Add results to date >>

The results to date haven’t been that inspiring, we’re only getting marginal improvements on our results from email.

It could either be the design of the push notification we’re using or maybe we were slightly behind that curve and people have started to ignore them.