“Your wishlist is on flat 40% sale” or “We’re on sale” – Which one do you think will work when you run an ad campaign? Which one relates/connects?
Well, of course, if you’re going to talk about my wishlist – I’ll be definitely interested.
You hear over and over that you should not be doing one-size-fits-all marketing but instead segmenting customers and tailoring messages.
Surprisingly, there are quite a lot of write-ups on essential customer segments that e-commerce brands must-have.
Some Internet’s famous segments that e-commerce brands must have are:
➡️ High spenders
➡️ Cart Abandoners
➡️ Coupon lovers
➡️ Thrifty shoppers
➡️ Indecisive shoppers
➡️ Loyal customers
➡️ Trendy customers, etc.
But is it possible to segment your audience on Facebook or other ad platforms?
In the last 9-10 months, we’ve been speaking to quite a lot of e-commerce marketers and the issues unanimously discussed are:
- ➡️ “Re-targeting ad campaigns are just not performing the way it used to be”.
- ➡️ “What do I do with 20-30% Facebook custom audience match rates?”
- ➡️ “We lost a couple of clients when their CAC increased by 30% in the mid-2021”.
These are our client’s words when we had interacted with them.
However, the ad platforms have some serious restrictions which do not give the marketers the power to go on full swing to strategize and segment these audiences as desired, because,
Facebook Custom audience match rate sucks
Let’s say, you have 20k users in the custom audience list who have “abandoned the cart beyond 7days” and upload the list to the audience manager.
But, Facebook could match only 25% which is close to 5k users from the total audience size. And it’s an open secret that Facebook’s custom audience is poor. Shhhh.
180-day cookie retention policy
Also, any segment that you create on Facebook will be deleted after 180 days and you cannot revive the data back as per the GDPR guidelines for advertising platforms.
Segmentation on Facebook is a lot of work
Manual work: Every time, when you want to run ads for any specific group of audience, you need to download, upload and set up the ad campaign all over again.
No customer behavior data: When a user lands on the website, they perform various actions and events. Rather than segmenting them based on the demographics, age group, they could be segmented based on their website behavior/actions.
For instance, if a user has viewed a couple of products in the footwear category, and left the page, we could segment and retarget them like “product page visited less than 3times” with messaging relevant to them that brings them back to the site.
Challenges to the marketers after privacy regulations and the iOS’14 update
Apple iOS’14+ updates have screwed the retargeting ad campaigns
In the current iOS’14+ update, Apple gives the user the choice of opting out of tracking. This makes it tough for Facebook to track user data – as Facebook no longer have access to the user behavior data like they used to have before the iOS’14 update.
Google is yet to screw the marketing ad campaigns
The challenge does not end here. Google announced, that, by early 2023 they will be phasing out third-party cookies from chrome.
During the first 10 months of the pandemic, we have seen 10 years of change. And the evolution is subjected to grow towards more user consent and privacy.
However, the only solution that we’re left with is collecting our own customer behavior data i.e.first-party data.
But why First-Party data is the only available solution?
We had conducted an experiment with our own blog visitors and had created two segments.
👉 Using Facebook pixel data of the blog visitors and
👉 First-party data of the blog visitors
And the results were:
Read on and teach yourselves to increase your custom audience match rate beyond 80%
Usually, digital marketers relied completely on Facebook and other ad platforms for tracking their website traffic and to access their own customer behavior data.
From the above experiment, it is as clear as crystal that relying on third-party cookies to perform any marketing activity is going to end in vain.
To save the campaign from going in vain, start collecting your customer behavior data i.e. First-party data. With the data collected, you can segment the audience as you require & use them on Facebook/Google or any other ad platforms — just like you do email marketing through CRM in which you select the users you want to send an email and schedule an email draft campaign. From the above experiments, we figured that the time has come to use advertising platforms for advertising only and not as your customer data host
Most businesses have not realized that they are in an inevitable and remarkable digital drift from third-party cookie tracking to owning their own customer behavior data (first-party data).
Also, BCG has conducted a study with Google and classified businesses into 4 stages based on the digital marketing maturity model and how smartly they use their own data.
What is Digital Marketing Maturity Model?
Digital marketing maturity refers to the ability of a business to consistently use technology to deliver the most relevant content to consumers at various touchpoints along the purchase journey, also referred to as multi-moment consumer contact.
Unfortunately, 63% of the e-commerce brands are stuck in stage 2 of digital marketing maturity.
In stage 2 of Digital Marketing Maturity Model, the marketers are powering Facebook pixel with First-Party data to run their ad campaigns. It implies the understanding of First-Party data among the marketers is still email id, contact number, or any form-filled data.
But when we say, First-Party data, it is your anonymous website visitors
Anybody who stumbles on your website is your first-party data.
Generally, 98% of the website visitors are anonymous visitors. They could have landed on your website by a Google ad, Facebook ad, or a social media meme or newspaper ad or television ad or organic search.
The majority of the anonymous visitors are the high intent audience who can be nurtured and pushed to the bottom of the funnel. But these anonymous users are stuck in the middle of the funnel.
Even 1-2% of conversions can scale up the revenue and improve the bottom of the funnel audience.
Read how activating the middle of the funnel audience can improve the ROAS by 2x
Activate and segment your mid-funnel: Stage 2 → Stage 3 of Digital Marketing Maturity
Move from old school segmentation to smart audience segmentation
Segmenting the audience based on the demographics and the default segments available on the advertising platforms like added to cart, checkout made are so old school.
Segmenting the audience based on their user journey and engaging them with relevant messaging brings the customer closer to conversion.
Middle of the funnel segmentation: “Personalised engagement”
Some of the mid-funnel segment examples to whom you can run personalised ads are
👉 Cart_abandoned for more than 30days
👉 Product_viewed_not_ added_to_cart
👉 Product _viewed_more than 3times
👉 Segment the users who have wishlisted for more than 10 products
👉 Segment the users who are first-time visitors and provide them “newbie discount codes”
India’s largest e-commerce fashion brand, W for Woman, implemented first-party data strategies and activated their mid-funnel audience. They saw increased match rates beyond 80% and tripled their ROAS. Check out to know W for Woman’s story.
Bottom of the funnel segmentation: “One step closer to conversion”
👉 Added_to_cart_not purchased
👉 Added_to_cart_before 30days
👉 Product wishlisted for more than 7 days
👉 Product wishlisted less than 3 days
Audience re-activation segmentation: “No more 180 days cookie retention fear”
You may have an audience built up during the festive season or during the sales season, with no 90 or 180 days cookie retention fear, you can bring them back. Because, you own your customer behavior data.
👉 Bring the Xmas and easter customers back to the funnel
👉 Bring the cyber Monday sales audience back to the funnel
👉 Bring back the one-time buyers who purchased 1 year back and re-activate & nurture them.
Stage 4 of the Digital Marketing Maturity Model is not really far – Mulitmoment
E-commerce marketers can predict and model the users based on their purchase history. One of our e-commerce clients has been segmenting and retargeting their users based on their purchase history like:
👉 Female customers who had higher cart values were retargeted for cosmetic products
👉 Customers who purchased top-wear clothes were retargeted for bottom-wears
👉 Predict the possible next purchase of customers based on their purchase history
👉 Predict the first purchase of a website visitor based on their website behavior
👉 Segmenting the plus-size customers based on the PDP(Product Detail Page) visits.
⚫ Moving forward the digital ecosystem is going towards privacy and consent. Relying on third-party cookie tracking is slowly dying and will eventually be gone.
⚫ Become your own customer behavior data host and segment the audience based on the website behavior to engage personalised.
⚫ Activate the mid-funnel audience and split the budget across the marketing funnel.
⚫ Personalize your customer engagement by advanced segmentation to progress towards the next stages of digital marketing maturity.