Optimizing Google Ads accounts for eCommerce can be easier than lead generation because the data you get can be more concrete, and you can get that concrete data quicker. Depending on the eCommerce industry, we tend to see the duration of purchase consideration differ from consumer to consumer. Some consumers will do their research and check out competitors before purchasing, while others will purchase items on the spot. The quick-purchase consumers make it easier to trace the revenue back to the click and know which keywords, ads, and campaigns are driving revenue and which are driving costs without revenue. This is the data you need in order to optimize towards profit and ROAS. For eCommerce stores with a higher price point, or that tend to have a longer consideration period, the time from the initial click to the final purchase (conversion lag) can be much longer and murkier. What do you do if the time lag to purchase is a month or longer?

Let’s say you pause a high-spending, low-revenue-generating keyword, only to find out two weeks later that the keyword was actually generating much more revenue than it initially showed. Have you just fudged up your account? Also, after 30 days, are you even able to correctly attribute that initial click of the campaign? If not, are you going to pause keywords/ads that are the start of the customer journey because you can't correctly attribute them to the final revenue? These are big issues for eCom shops that have longer sales cycles, so how can you avoid turning off pieces (keywords, ads, campaigns, etc) that are crucial to your shop's success because they don’t SEEM to be driving sales?

The way we deal with this time-lag issue is through micro-conversions. These are actions that occur on your site that aren’t a purchase but could be the first step a user takes to becoming a purchaser on your site. On most sites with a longer duration between the initial visit and purchase, there are things that a user can do to help make that final decision. Let’s say you sell custom furniture, something a user could take action on your site would be to “get a quote” or “get an estimate” where they can see how much a certain item may cost them to purchase. This could be considered as a micro conversion which shows the user is getting closer to a final purchase.

In a separate scenario, let’s say you’re looking into buying a sauna. There are several things to consider such as the design, its dimensions, where you want to put it, utilizing proper energy sources, etc. We know that for this type of purchase, you may need to ask several questions through a form or chatbot. This could also be considered a micro-conversion which shows that this user is closer to a purchase (and may be deemed “more qualified”) than users that have just gone to your site and not asked questions.

I think you are getting the gist but one more example, just for fun. Rachel Davis, on our team here recently purchased astroturf for her yard (which she gloats about any time I have to mow my lawn). When she was going through her purchasing decision, one action she took was to go to a few different turf sellers online and request samples. Samples are a common way to understand the feel, color, etc of a very expensive product without having to purchase the whole item. It’s also another micro-conversion to be considered.

Ok, so you have some micro-conversions on your site, and that’s great, but how does this help us optimize the account toward more revenue or possibly a higher ROAS (just remember ROAS may not always be the best goal for your eCommerce account)?

Well first, you need to make sure that you are tracking those micro-conversions. For us, we find that using GTM to fire GA4 Event tags based on clicks or form submissions works best. Once those events start firing, you can then import them into Google Ads and start to see the conversions on a keyword, ad group, and campaign level. I know what you are thinking now, “But Shaun, don't you always say that treating all leads the same and maximizing quantity isn't the best way?!” “Yes, you are getting ahead of me.”

Now that we have micro-conversions tracking and importing, we need to start putting values on these leads. Is a chatbot click the same value as someone ordering samples? Probably not. So let’s not treat them that way. We have found that the best way to value these micro-conversions is to ask for and use the clients' own data (hopefully they have stored it). With GDPR and various privacy laws, you need to be careful here so make sure you aren’t asking for anything that could get you or your client in trouble (if you are unsure just send these instructions to your client and have them do it - better safe than sorry). But in essence what you are going to do is:

1. line up information from the original form (an email or unique identifier preferably) to the final sales to see how many people that submitted a micro-conversion ended up becoming a customer.
2. Use at least a year’s worth of data and end your micro-conversions a month sooner than the purchasers.
3. If you're doing this in February, ask for last year’s micro-conversion number and then ask for sales data through January. That way if someone converted a micro-conversion in December, you will know if they became a customer in January.
4. Divide the number of users that purchased (only that started with that specific micro-conversion) by the total number of micro-conversion converters to come up with a conversion rate.

5. Then find the average purchase amount for the users that started with that micro-conversion to come up with an AOV.

6. Multiply the AOV with the conversion rate and you have the value of your micro-conversion.

Ok, that was a lot! Now let’s walk through an example to showcase that it’s not as complicated as it sounds. For this example, let’s say we are running a custom furniture company and are trying to figure out the conversion value for wood samples.

To start, we grab everyone that has ordered a sample within the past 12 months. We also pull completed purchases within the past 13 months and match those who ordered samples with those who ended up buying a custom piece of furniture. Let’s say 1,000 people ordered samples in this period and out of the 1,000, 350 purchased a piece of furniture. The average purchase amount for those 350 people was $1,250.

• First, we find the conversion rate 350/1,000=.35 or 35%
• Now, we take the conversion rate and multiply it by the AOV of the purchasers who first ordered a sample $1,250*35% = $437.50
• Therefore each sample is worth $437.50

• We do this same math for each of the micro-conversions that we have identified and tracked, and we add that value to the conversion either in GA4 or Google Ads. Then, we can start optimizing that goal towards ROAS.