Agile Marketing is a concept I find often lauded in blogs and news sites, but rarely do I see any informative content about how to actually transition to a lean marketing approach.

It wasnt until I started reading Lean Startup books like ‘Running Lean’ (By Ash Maurya) and The Lean Startup (by Eric Ries) that I was truly able to understand how to run an agile marketing team.

The purpose of this post is to outline how I approach agile marketing, in the hope that maybe it’ll benefit someone else.

Introduction: Ongoings and Experiments

When practicing agile marketing, work can be divided into two categories: ongoings and experiments.

Ongoing work refers to work that needs to be carried out on an ongoing, recurring basis. Examples include:

• Regularly creating quality blog posts to enhance SEO, promote social discovery and increase entry points
• Regularly creating and distributing cornerstone content to generate leads
• Regularly sending email newsletters or undertaking lifecycle email marketing
• Regularly listening and engaging on social media

Experiments on the contrary, are one-off units of work we undertake in order to help us improve the single metric we are currently focusing on. These may include:

• Re-designing parts of your website or application
• Launching new features
• Implementing lifecycle emails

It’s important not to approach experiments on a hunch or assumptions, but to base them on actual user data. More on that later though….

Ongoings

Ongoings refer to work that needs to be completed on an ongoing, recurring basis on top of the experiments you may be running.

The definition of ongoing work is different for every business, and depends on your marketing strategy, customer acquisition channels, business model, partners, etc. Generally speaking though, ongoing work could include:

• Regular production of informative, educational blog posts – Most SaaS companies participate in Inbound Marketing as it’s a brilliant, scalable way of acquiring customers at a low CAC. While it may not necessarily cost a lot of money, it does cost a lot of time. Best practices for blogging are outside the scope of this article, but if you’re interested in learning more, I’d suggest reading the works of Neil Patel at Quicksprout, The Daily Egg or KISSmetrics blog.
• Regular monitoring and updating of social media accounts – Social Media can be a great way of getting your content into the hands of your potential customers in an organic manner. Social media ongoings can include the posting & sharing of our blog content, the curation and sharing of other relevant content and the ongoing engagement in conversations.
• Maintain regular email contact – Particularly for B2B SaaS products, email marketing can be brutually effective when done correctly, especially when it’s hyper-personalised based on the users actions within your application. Again this is outside the scope of this post, but for more information on this i’d recommend checking out the blogs of Vero and Customer.io.

Experiments

Experiments refer to one-off units of work that are designed to progress a single metric that is currently being focused on.

The concept of experiments is that you pick a specific metric to focus on (usually it’s a good idea to pick the metric that will give you the most return for the least amount of effort), then you run experiments to improve that metric until you either reach the end of the timebox or achieve your goal.

The process for identifying, executing and validating experiments is outlined below.

1. Define a single metric.

To begin with, a single metric to focus on must be identified. This is critical in order to ensure your limited marketing resources are highly focused on an area identified to return the highest ROI in the shortest amount of time. Using your analytics system (particularly your primary visit site – signup – activation – purchase funnel), you should be able to identify where the biggest blockage point is and make that the single metric worth focusing on (I.e. Signup – Activation Rate).

It is also important to set an exit criteria at which point in time you move on to the next key metric. This can either be by achieving the goal state or hitting the timebox limit.

• Goal state – A goal state must be set in order for you to map your progress. A goal state should be specific, measureable and attainable such as ‘50% Signup – Activation rate’.
• Time box – An exit criteria of a specific time may also be implemented. This is because testing and experiments generally suffer from diminishing returns, in that the closer you get to a perfect state the less effective your experiments become. Set a timebox limit that allows for enough experiments to be carried out but keeps progress in line with business growth projections.

An effective way of setting goal state and timeboxes is to visualize the funnel in an excel spreadsheet and make modifications to the metric in question to see its effects on the rest of the funnel, and then comparing this to growth objectives.

2. Identify the blockage points.

Once a single metric is identified, the next step is to breakdown the steps/stages of that particular micro-funnel (For instance, if the Activation Rate is the identified metric then the ‘micro-steps’ to that would whatever steps you’ve identified as your activation steps).

By looking at this funnel (and deeper into the process if possible), you can identify the key areas where people are falling off and prioritize experiments in those areas.

3. Identify reasons for dropoff

Once the key areas for drop off have been identified, it is important to get feedback from customers as to why this is occurring rather than make unfounded assumptions.

There are multiple ways this can be achieved, which are outlined below:

• Call – A customer lifecycle analytics package like Kissmetrics will allow you to pull up a list of users who got stuck in an identified state (I.e. Have done event ‘Signed Up’ but have not done event ‘Paid’). Assuming your recording your customers phone numbers at signup you can potentially call the customers to ascertain deep levels of feedback on what went wrong.
• Email – Using the same list, you can potentially email all your customers and either provide them a link to a survey or better yet, just give them one or two questions in the email and get them to simply reply to you.
• Qualaroo – Qualaroo is a micro-survey tool that can display a ‘mini-survey’ to a user somewhere on the page. It can easily be deployed within your application to ask your users questions like ‘What stopped you becoming a paid customer’, and presenting them either a free text box or multiple choice questions which they can use to respond.

You may have noticed the above list progresses from qualitative to quantitative feedback mediums. Depending on complexity and importance of problem, it may be worth using multiple mediums in a waterfall format to first understand the problem qualitatively and then validate it quantitatively.

4. Develop falsifiable hypotheses and define experiments

Once the dropoff points have been identified and reasons are known, we can then create falsifiable hypotheses and design experiments that when implemented, should hopefully enhance the key metric.

If you’re not familiar with the term Falsifiable Hypotheses, they are hypotheses that are specifically worded so that they can either be ‘proven’ or falsified’. A good example would be ‘Adding customer logos to the signup page will improve signup rate to 20%. As you can see here, this one sentence defines the experiment you are going to run as well as the expected result. Ash Maurya provides a brilliant template for creating and documenting falsifiable hypotheses and i’d thoroughly recommending checking it out over at his blog.

5. Carry out experiments

This aspect will differ largely depending on the type of experiment

6. Record results and learnings

Regardless of whether an experiment returns a positive result in the key metric, it is important to document the results and any learnings we may have received from it. This will not only help us to document the process, but will allow us to build up a library of learnings we can refer back too.

The same template for recording experiments (The Experiment Report) can be used for documenting results and insights. In this case, the right hand column needs to be filled out and the report filed against the experiment in Trello.

6. Iterate and repeat

The final step of the process is to use the learnings and results from the previous experiment to iterate on the overall plan, modifying any upcoming experiment or changing priorities based on the new information. If relevant, you should also update the buyer personas as well.

Do you practice agile marketing in your organisation? Is there anything I missed? Would love to hear your comments below….