Scaling Your Email Campaign Scientifically

This is very difficult to do with just 10 subscribers and 3 sales. It would be difficult to do if we had 100 subscribers and 3 sales. The easier scenario would be if we have 1,000 subscribers and 30 sales. And even easier to do if we had 10,000 subscribers and 300 sales.

We will use an imaginary 20 email sequence in this next scenario. Let‚Äôs say it’s 14 days and 20 emails. Let’s say that our open rate on each email is on average about 20%. Some emails will be higher, some may be lower than that. What this means is that the average person that goes through your campaign will open your first 20 emails with an average open rate of about 20%. We could use click through rate if we wanted. I won’t be using that for this scenario because not every email has clicks in it so you won‚Äôt have a click through rate. However, for emails that do have clicks in them, I usually evaluate the click through rate and not the open rate. It probably doesn’t really matter, the exposure to the email is the important part.

If you have 10,000 in your campaign, you have an average of 20% open rate in all of your emails. That’s everyone, buyers and non-buyers. Then we look at the buyers and we say, “How are buyers different from non-buyers?” What we can do is look at the open rate and the click through rate for an individual email. Don‚Äôt do the math for non-buyers vs buyers. For this scenario, I would recommend doing the math on the total campaign vs buyers. If 3% bought and 97% did not buy, if I just look at the aggregate, I would be so close to the number anyway, it would be a little more time consuming to calculate the non-buyers.

We’re going to take the average open rate for email 5, just for this example, let’s say it has a 20% average open rate. If someone bought, there’s a 50% chance that they opened that email, so what does that tell us about this email? It tells us that this email is probably contributing to the purchase. What we are saying is 20% overall open it, but 50% of buyers opened it. If we were to do the math and look at non-buyers vs buyers instead of buyers vs. overall, you might find that the non-buyers are 19% open rate and the buyers are 50% open rate.

You can see how close the non-buyers and the “overall” metric is; that’s why I wouldn’t recommend spending the extra time trying to compute the buyers vs non-buyers.

This tells us that if someone opens that email, they’re probably going to be more likely to buy from us.

Let‚Äôs say we look at email 6. It has a 20% open rate for everybody. It only has a 5% open rate for buyers, so that would probably tell me that that email, when opened by potential buyers, turns them off and they now become non-buyers! What do I do now with this email? I would get rid of it! Some people might say, “Let’s look at the email and try to find out what’s wrong with it.” It would take you a lot less time to write a new email at this point than it would be spending hours trying to figure out what’s wrong with the original email.

Let’s look at another scenario: Email 7, 20% open rate across the board, 75% open rate for buyers. I would keep this one.

Email 8, 20% open rate across the board, 2% open rate for buyers, this email would need to be redone, it’s not driving any sales.

At the end of the day, we have 10 emails that are taking away from sales, so we would discard those and redo them. Then we have 10 emails that are contributing to sales, so we keep those.

We now have a decision to make:

Do we write replacement emails?
Do we try to run the campaign with just 10 emails to another 10,000 people?
Do we split test it and see what happens?
Do we get more conversions with just the 10 performers than we did before?

My guess is that we probably will. Split testing is a good idea, so here are some options:

Have one group of people go through the optimized 10 email campaign vs.

Another campaign that has those 10 emails in it plus 10 brand new emails

Another option would be to look at broadcast emails that have the 50% to 90% open rates in them and place them in our campaign.
We don’t want to move all of our best emails forward. You want to keep some to close with because most people don’t buy the $1000 package the first day. My experience is that they buy within 3-18 days. That means that one person might buy it within 3 days, another may buy it on the 18th day, but the average person buys between days 11-14.

So, you want to save your best emails for later on and for the last day. I have discovered that if you haven’t captured your audience‚Äôs trust by the 14th day, you may not at all with this campaign. You should have their trust by the 14th day. The key is to constantly tweak and work the campaign, always looking at your numbers.

I would recommend doing this about every few days, looking at what is making people buy and making them not buy.

For an example on tweaking: In one of my campaigns, I have set up a payment option, but I am going to take that option out. I am finding that the people who are taking that option are not committed to doing the work. They don’t seem to be working as hard, and I find that when people aren’t working as hard, they‚Äôre not typically getting the same results. That leads to them dropping out. They‚Äôre not staying in as long.

Even those that wait to purchase within the 14-18 days range are purchasing with the full payment option – the $1000 level. I made the mistake of thinking that the ones who were purchasing at the 14 day point were choosing the payment option but that‚Äôs not the case. They were actually buying the full payment option and becoming profitable customers because they really experienced success with my training.

So, I’ll be getting rid of the payment option and start again.

This is what you need to do with your campaigns, continuing to tweak it and make adjustments over time.