The best way I can track my Adwords leads/customers is by using UTM paramenters on my links, and based on the data I collected this is what it currently shows me. I segmented my data to show all Adwords customers and then created a cohort analysi based on the customer's signup date. I then took the monthly amounts I spent on Adwords and compared it to all of the profit I received from each of these customer signup date cohorts and on average it is showing me a ROI of -27%, so I ended up losing money from the customers I acquire through Adwords. Then I go and calculate my LTV based on the same data I collected (only Adwords customers), and based on a total average I come up with a $114 LTV profit. There is no way I can spend $114 to acquire a new customer when my ROI customer signup cohorts are showing that I'm losing money on Adwords. I also did a LTV calculation on my best customers from this same Adwords customer data and I got $487 LTV and for my worst customers I got $30 LTV. Now the only LTV that looks closer to normal is my worst customer LTV of $30, but this is frustrating to see on the total average an LTV of $114 becasue if I would have spend that much to acquire a new customer I would definitely be losing a lot of money. Luckily, all my best customers come from other links that I don't control that do not have UTM paramenters; I'm guessing through organic search; so I don't know if my Adwords are helping bring these type of customers in or if I should just stop with Adwords advertising?
Do you know how your best customers are finding you through adwords? If you have a big enough data set there's likely some commonality.
It's a gross oversimplification but if you can track them from start to finish, there's no reason you should have to continue acquiring the $30 customers.
I think you might be comparing apples to oranges. The cohort ROI report will be using individual conversions, whereas the LTV report will be using multiple conversions. If your revenue is highly driven by recurring revenue, then you could end up in the situation you're describing.
For example, if you sell an average of 5 $100 items to a given customer, your LTV might be $500. However, if you spend $150 to acquire that customer, then you'd see those reports produce a negative ROI, with a higher LTV.
I wouldn't start giving AdWords credit for non-tagged sales. Rather, determine what your target CPA is for a transaction, averaged across your transactions (regardless of how many past orders they have, unless you're prepared to do some overly complicated targeting). Then, you'll never run up against the challenge of "should I just stop", as you can always optimize your bids to target that specific target.
If, however, you can only compete in your niche if you consider the LTV, then you'll want to model your customers, and exclude the outliers on either end. Build a plausible "model customer", using some median values, and target their LTV like it was an AOV.
Once you have an AOV (literal or LTV-based), then you just need to know how much of that you want to spend. This percent is called the Cost of Sale (COS). Let's say your AOV is $300, and your COS target, based on your budget, is 30%. That means you can spend $90 per sale within that AdGroup, Product Group, or other biddable entity in your account.
With a $90 CPA, you can arrive at a reasonable bid by multiplying by your Conversion Rate. If your conversion rate is 5%, then you're saying that it takes about 20 clicks to get a sale (in aggregate), so you can only spend 1/20th of that $90 for each of those clicks. That's a CPC target of $4.50.
If your average CPCs are coming in lower than that, you're going to beat your ROI target, but you may be giving up market share. If your average is higher, then you might be capturing a lot of market, but you'll be short of your ROI target.
If you update those bids regularly, then they'll tend to normalize at producing what ever return you're aiming for, with the proportional share of market.
If you'd like to get a little more help with the specifics of your situation, feel free to reach out. Here's my VIP link, so it'd be on the house: https://clarity.fm/roysteves/statbid
I think with a $450 swing between your highest value and lowest value customers, it's not instructive to bunch everyone together and average things out. I'd break up the cohorts a bit and run an analysis like that. Whether it be by demographic, order type, order size, net profit...you need to find some more granular veins of data in there in order to make better marketing decisions.