A few months back, I wrote about using data to determine the timing, content, and impact of your email marketing campaigns (See: 6 Steps to Putting Data to Work in Email). In the last few months, the element I find myself discussing most with colleagues and clients is the latter: What data can we use to attribute the impact of our hard working email marketing campaigns?
When it comes to challenges in attribution, I’ve heard it all:
- We’re B2B service-based company with a long lead cycle and a personally closed sale.
- We’re a restaurant with no online ordering, online reservations or online sale capabilities at all.
- We’re an eCommerce company (perfect!), but we don’t see our web analytics reporting (what??).
So I’ve started my own sliding scale of things that (truly) every email marketer can use, all the way up to the latest and greatest tech (that’s more of an investment).
Email Marketing Attribution Ideas for Every Business Model
LEVEL 1: Email Metrics from your Email Service Provider or Marketing Automation Platform.
EVERYONE can do this one. While it’s not revenue attribution, you can at the very least learn which of your campaigns was likely to drive the most results based on who took an indicating action, i.e. clicked on a call to action like Buy Now, Schedule a Demo, Print Coupon, Find This Near You, etc.
You can also do the age-old correlative attribution: When we send an email to market A but not market B (and they’re comparable markets in as many ways as possible), and market A shows higher sales, we can assume that email had a role in the lift in results.
LEVEL 2: Google Analytics without Online Revenue.
Even if you don’t sell anything online, you can still use Google Analytics to determine mid-funnel indicators like site traffic and time on site by lead source to tell your email marketing success story. I love showing the Site Traffic report for the year and seeing the spikes around our monthly newsletter or the start of a media campaign.
LEVEL 2B: Google Analytics Conversions without Online Revenue.
For B2B companies or organizations with long lead cycles, even if you don’t sell online, you can still set up Google Analytics to watch conversions as if they had a revenue value. This one is a slight step up from Level 2 in that you’ll need to have the data to determine the true value of a web lead. Are they qualified? What % do you close and what is the average value of that contract? Work backwards to find the value of every lead that comes in via each page of your website, then assign those lead form conversions that value. Then Google Analytics acts a bit more like an eCommerce report (see Level 3, below), and you can determine things like best performing campaign by time on site or pages visited or unique visitors.
Is there a “Find a location” page that they visited after viewing a product, menu page, or ad circular? Is there a social share feature on a product page that they clicked on? These could indicate a preference or intent to buy that came from their engagement that started with email.
For those with a physical location where customers buy, Google Analytics can be paired with asking/incentivizing a customer to tell you where they heard of you…
LEVEL 2C: Offline Customer-Reported Results
Using coupons to attribute sales to an email campaign is the easiest and clearest option, IF you have a consistent POS that eventually cycles that data back into your master database or directly into your ESP/MAP. This gets to be more like Level 3 reporting if you can track each individual coupon redeemer back to your master database and/or ESP/MAP. (You could also use the low-tech of a coupon code or offer ONLY available to email – so that in the POS system you can see how many redeemed, even if you don’t know which person specifically redeemed it.)
If you don’t discount/offer coupons, you/your staff can simply ASK “Where did you hear about us?”
If you have a Point of Sale system that can (a) take in customer data like email address or phone number and (b) send that information back to your master database, you can go with the ever-popular “Can we get an email address to send you future offers?” or “What’s your phone number?”
Loyalty programs can incentivize your customer to help you track what campaigns were sent to them and pair it with what they’re buying. This is usually correlative data, but it can be useful in determining big campaign influences. For example, what % of your shoppers got a promotional email within a week before shopping? Or, better yet, if you sent an email promoting a shampoo sale, and one of your subscribers opened it, and then comes in and buys shampoo… it’s fair to say that the email had an impact on that sale.
NOTE: With this type of correlative data, and in fact with most campaigns, you likely can’t presume that email was 100% responsible for the purchases of an email subscriber. You can, however, use your loyalty program or email/phone data to pull reports that can tell you what the average customer spent compared to what the average customer who subscribed to emails spent. That’s also a good indicator of the value of your program, though it’s still correlative and not necessary proof that emails CAUSED all of those sales – it could be that our best shoppers are likely to be both big spend spenders and email subscribers.
LEVEL 3: Google Analytics Revenue by Source/Campaign
GA’s Revenue by Source and Revenue by Campaign reports are the gold standard for me. When we have this, I pore over the data, seeing just how much revenue my hard work has created for the company! I’ve seen big swings in revenue driven by email between individual sends, finding our highest and lowest performers for the year.
The same rules about sharing attribution with other channels – especially non-digital channels – apply here. Were your email subscribers influenced by a radio ad or billboard before they clicked on the link that our email so conveniently sent to them?
Some email platforms like Klaviyo, with its seamless integration to Shopify, can also show total revenues attributed to each email or campaign.
LEVEL 3E(merging): Verified Walk-in or “Footfall Attribution”
While this doesn’t tie revenue to visitors, and might really fall into Level 2, it is one of the newer methods of attribution that doesn’t require a customer to be involved in “reporting” that they came to your store.
You may have heard that Facebook offers this for their advertisers: They can tell, using pixel placement within the displayed ad, when the device where someone saw an ad on Facebook walked into one of your physical locations.
This “verified walk-in” or sometimes called “footfall attribution” is available outside of Facebook as well. Used largely by media teams, this is one we should be borrowing for email marketing attribution! (See my recent OI article on more reasons Why Email Marketers Should Befriend the Media Team.)
To get started, check out what vendors like SITO Mobile, Cubeiq, and Placed offer in terms of being able to “buy the data” for verified walk-in (as opposed to requiring that you place media through them). BONUS if you can use the device ID (unique to the phone or device) provided in these vendors’ data to correlate the walk-in with a known subscriber in your email subscriber database.
With that level of detail, the future of creepy data is officially here. But if we can prove to our shoppers that it has value for them – with more relevant offers, and ads that stop running when we know you’ve purchased – AND we can make it feel seamless instead of overt, this attribution is as exciting for customers as it is for us marketers.