I have came across an ad which presented a local hotel offer that appeared on the YouTube feed of my mobile app. The ad could have been served to me be based on location, potential consumers who are similar to me and my search history. It could also have identified my location hence presenting to me local hotel offers, which might not be the case in the past, but given the pandemic where staycation is gaining popularity, it could have been searched by many local users. I also remember myself searching for local hotel offers on Google while logged into my account on my laptop, which might have been captured by the web cookies. Hence, even when I opened the YouTube app on my phone, my id was still identified since I am logged into YouTube with the same Google account.
I think the advertising campaign’s effectiveness would depend on the business goal. If purpose of the campaign is to boost sales, a high conversion rate and total value of purchase would be the desired outcome; while if it is just to generate awareness about the brand or product, a high click-through rate (CTR) of the ad served could be satisfactory enough. Under the goal of generating brand awareness, even for consumers who do not have the need to initiate an immediate purchasing behaviour, they will have the name of the hotel on top of their mind, so that when the need arises, they are likely to make the purchasing decision.
While conversion demonstrates quality of the landing page, CTR depends on quality of the ad itself and time of the ad being served. It could be possible that at night, when people have the luxury of time to plan for their staycation, the cost per impression and cost per click of the ad might be higher. But for both, the type of audience reached would affect the result. Ads should be served to targeted audience with higher likelihood of clicking through, being converted and making higher value purchases. Meta pixel would be useful as it provides a range of data on specific past interactions with the website made by users at different stages of the purchasing funnel.
The purchasing funnel presents four stages within the consumer journey — Awareness, Consideration, Purchase and Retention.
The top of the funnel includes awareness and discovery. The action tracked would be the initial page view. The user clicked an ad and landed on the home page, showing initial curiosity. Meta is able to use the profiles of these site visitors to find lookalike audiences —new users across Facebook/Instagram with similar demographics and online behaviours. Exclusion filtering is also achievable through Meta pixels, to exclude recent site visitors from broad “Awareness” campaigns budget is not wasted showing introductory ads to people who already know the brand.
The middle of the funnel includes consideration and interest. The action tracked could be searching for items or browsing specific products, which show that consumers are evaluating options. If consumers do not proceed to add the products to their shopping cart, retargeting ads can be set up to promote products to them again based on their browsing history.
The bottom of the funnel includes add-to-cart and checkout where consumers demonstrates high purchasing intent. Losing customers who are already reaching the end of the funnel would be exceptionally unworthy. Hence, ads of the exact same product can be served to people who have added to their wish lists or abandoned in their shopping carts to remind them to complete the purchase. Retargeting ads can be set up again with limited-time discount codes, free shipping or cash-back offers. For example, sending an email to consumers who added product to their carts but did not check out within the past 3 days.
Post purchase stage of the funnel includes loyalty and retention. Complementary products can be offered to consumers who just made a purchase, for example, a laptop case after they purchased a laptop. Facebook pixels can also build Lookalike Audiences derived specifically from highest-spending customers.
Meta pixels is also able to track event volumes for events including view, add to cart and checkout. By demonstrating the proportion of consumers who move towards the lower end of the funnel, brands can reflect on friction points on their website that prevent consumers from making the purchase. For example, consumers who abandoned their shopping cart at the checkout page, they could have been deterred by an overly expensive shipping cost. For consumers who has browsed a lot of products but did not add to cart, it could have been because of an overwhelming volume of products available or an overly high price. Maybe brands can organize their offerings into different categories easy for consumers to navigate and find out what they need, or offer discounts for product bundled such as offering a set of products. For example, a product bundle can be used for a complete skincare routine from cleansing, exfoliating and moisturising.
To improve CTR, ads can be delivered tailoring to users’ interests based on general product categories of all their past browsing history on Google, whether or not they have visited the advertiser’s site. Since Meta pixel can also identify the same user across different devices, data will show whether users tend to view an ad on a mobile but switch to a desktop before buying, or the other way around. This could help advertisers redistribute the placement of ads for audience who are more likely to be converted when they see banner ads on desktop browsers, or mobile phones including splash ads that are displayed when a certain app is opened. Depending comparing the different response on mobile and desktop, advertisers can redistribute their budget more efficiently.
As such, I believe that data tracked by Meta pixel would help optimize the delivery of ads to customers at different stages of the purchasing funnel to push them towards the later part of the consumer journey, yielding higher CTR for effective awareness campaigns, as well as more conversions and higher-value purchases for a sales promotion.
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