Data-Based Decision-Making

Before I started focusing on optimizing for outcomes, I had started a YouTube channel producing how-to videos related to automation and efficiency improvements in business. As I shifted my focus, the time needed to produce the videos was consumed by other activities. Having gotten many things in order in the last couple of months I was ready to tackle video again.

Since my old channel still had some subscribers and videos that were generating some views through organic search, I thought I could just continue to produce videos for that channel, leveraging the small base I had already established.

Modest Initial Goals

When I started the channel I didn’t have lofty goals but figured it would be a good way to start generating a little bit of money and establish a decent audience. Between ad revenue and affiliate marketing, I figured I could add some additional authority specific to technology, and a few thousand dollars a month into my pocket.

I made a new video last week after spending some time researching keywords and related topics. I wanted to make a video specific to ActiveCampaign which is software that I use for a CRM and marketing automation and researched to find some of the more common searches specific to ActiveCampaign.

I produced a good quality eight-minute video that showed how to set up simple automation to repeat an email on a regular cadence. After a week it’s gotten two views. This was a little bit disheartening, to say the least.

Poor Results? Change Something

As I thought about what I could do to make it better, I thought it would be a good idea to spend a little bit of time gathering some more data so I could better define a reasonable outcome.

I started by looking at how many subscribers ActiveCampaign has itself. The number was much lower than I would’ve expected with 2500 subscribers. I also looked at how many views their videos had and was again surprised by the low numbers. Many of their videos are a year older or more and have less than 1000 views. Their big “start here” video only has 14,000 views.

My first thought was that ActiveCampaign is a fairly niche product so other tech channels would have lots more subscribers and tons more views. As I looked around I found that to not be true. I looked at several other how to software and tech channels and found that most of them have under 10,000 subscribers and an average between 1000 to 3000 views per video.

The next thing I did was to look at how much the average YouTube channel makes from advertising revenue. The numbers available online vary but most say $1 to $3 per 1000 views is standard.

Do Some Math with the Data

I then did some math with all of these numbers and my planned number of videos for a year. Even if I used the high numbers the data showed that I would not reach the outcomes I initially thought I could get. At $3 per thousand views and an average video getting 3000 views that means each video would make me $9. With a video taking about four hours from start to finish including the planning filming and editing, I’d make about $2 an hour. If I made one video per week I would generate a whopping $468 per year.

I didn’t do any math specific to the affiliate revenue potential but knowing that it would take a few thousand sign-ups to generate a meaningful amount of recurring revenue, coupled with the low viewership of ActiveCampaign itself, I can safely assume the returns would be small.

Data Is More Important Than Feelings

This exercise highlights the importance of using data as opposed to thoughts and feelings. My thoughts and the beginning seemed very reasonable. Again, I didn’t have crazy goals or anything that I thought was unrealistic. It seemed sensible that I could work hard and be consistent over time and eventually generate a couple of thousand dollars a month.

Once I looked at the numbers I could see that my initial assumptions were way off base. For me to make $2000 a month, I’d have to make 50 videos every week and have them all hit 3000+ views. Obviously, this is not realistic.

Realignment Needed

With good data in hand, I can now think about how YouTube could fit in my future business. Defining an outcome of ad and affiliate revenue is not realistic. I then questioned what potential value would it have if not add and affiliate revenue. People are using YouTube successfully and it does have a place in business strategy so I needed to identify how it fits into my strategy.

I started to think about different ways I could leverage YouTube. I also researched the way other businesses are using YouTube to generate income. The conclusion that I came to is that it’s better used as a lead magnet of sorts, generating traffic into my sales funnel.

Rerun the Numbers with New Assumptions

Here are some different numbers for you. Assume I make the same one video per week and get 3000 views per video. If I filter that traffic through my sales funnel and get .1% conversion on that traffic for a $47 program that I sell, each video will make me $141. That’s much better than $9 that I would get from ad revenue and the conversion number is very conservative. Now, one video per week will produce $7000+ in a year.

$7000 per year certainly isn’t enough to retire on, but it’s a good start and much more meaningful than $468. With that, I can work on refining my sales cycle to get a higher conversion percentage. I can also produce and release additional products that will also make me more money per video.

Because of this exercise, I am also rethinking having the tech channel as a separate entity. Because my analysis showed me that for YouTube to be viable I need to funnel it into products, having a separate tech channel no longer makes sense. I don’t want to have a tech channel with one branding funnel into a website and products with different branding as that would create a confusing customer experience. I will, therefore, need to restart the YouTube channel with the same branding as my website and products.

Because of data-based decision-making, I now have better defined outcomes specific to how I’m using YouTube that are better aligned with the outcomes I need for my business. My process specific to traffic generation is now better aligned with the outcomes I need throughout my business.

To Summarize

  • I had poorly defined outcomes based on bad assumptions and feelings
  • When I decided to use data-based decision-making, it was clear the outcomes I defined were incorrect
  • The data helped me rethink what outcomes were realistic and I read defined what I wanted out of YouTube to align with those outcomes
  • With newly defined outcomes specific to my traffic generation activities I was able to realign the steps I was taking to the new outcomes

Actions for You

  • Identify an activity in your business that isn’t producing the results you expect
  • If you don’t have clearly defined desired outcomes for the activity, define your desired outcomes
  • Test the assumptions that you’ve made about being able to reach your desired outcomes by identifying and measuring the outputs you would need to reach that outcome
  • If you see a problem with your defined desired outcomes or misalignment in how you are executing the activity, make adjustments as needed
  • If you do not see a problem there are a few things you can try
    • Talk through your logic with a trusted advisor
    • Look at your activities that are further upstream (activities that happen before the activity you’re trying to fix)
    • Book time with us and we will help you talk through what’s not working and how to fix it

If you’re looking for extra guidance on how to apply this or other tools in your business, you can book a 15 minute call with me for $95 here.

If you have a bigger need, please email me and we can discuss how I can best help you Optimize for Outcomes.

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