This is a question we often get when we’re running a lead or conversion optimised campaign for a client. In such a campaign, we use machine learning algorithms in platforms like Meta (Facebook or Instagram) and Google to target the client’s ads (and thus its budget) at the customers who are most likely to convert.
Here’s how it works: We add tags to your website. Then we set up conversion events, which are the actions we want visitors to perform, such as completing a lead form on your site. Platforms such as Google or Facebook use the data they constantly collect about their users and data about your website’s visitors to decide which users they’ll target with your ad.
This includes behavioural data and intent signals, which enable the platform to determine how likely a user is to fill in your form or buy a product from your website. If you or your boss keep clicking on your ad or visiting your website, the algorithms will determine that you’re unlikely to convert. The platform will thus stop showing your ad to you to minimise wasted spend.
The machine learning is doing its job by showing ads to people who are most likely to convert and saving you money by not showing them to those who aren’t likely to perform your desired action. But if you’re running an awareness or prospecting campaign, you’ll want to achieve a broader reach. We would set up your campaign to reach more people and drive new audiences to your website.
Most of our clients have product categories or services that are higher priority or more profitable to the business than others. They often ask if they can split their budget across different products, services or categories, focusing more spend on the most valuable products and services, and less on the others. In our experience, this approach risks diluting the budget and hindering overall campaign performance. We find that it is more efficient to allow the ad platforms to auto-optimise for the best performing product or ad execution. This ensures you’re getting the conversions at the best possible cost per conversion. Google helps advertisers to maximise conversion value through its value-based bidding solution, which lets companies bid towards business priorities, such as growing profit or revenue.
Before major platforms like Meta and Google started to dominate the web, advertisers would book ads on websites and apps at a fixed cost. They would choose which ones to advertise on based on the publisher’s or industry audience data, matching their campaigns to the sites where they believed they would find their prospects and customers.
But programmatic advertising allows us to be more accurate and efficient with our targeting. Programmatic platforms collect data such as intent signals, interests and behaviour about users across the web. They use this data to group audiences by their interests, what they’re in-market for, or which product or service pages they’ve viewed on your site.
We can then target the audiences that are most relevant to you across whichever websites and apps they spend time on. CEOs, for example, don’t only go to business websites and LinkedIn. They have a life outside of work and may visit a range of websites, apps and social media channels. Neglecting these channels could mean missing an opportunity to engage with them.
The answer to this question lies in the attribution model you use. If you’re using a last-click attribution model, Google will get all the credit if the last channel a user engaged with before converting was a Google search ad. But the user may have watched your video ad on YouTube, clicked on a Facebook ad, and browsed your website before they were ready to buy. Without those engagements, they would not have searched for your business a week later, clicked on your ad and converted.
Putting in place tools and processes for more accurate attribution modelling can help you improve campaign performance and make more informed decisions about allocating budget. You would use historical data to assign credit for sales and conversions to each touchpoint in each conversion path. The tech helps you understand how different channels work together to achieve conversions.
A good tool will enable you to not only see each channel that played a role in the customer journey, but will also guide you on where you are under or overspending and which channels you should allocate budget to. By identifying successful channels and tactics, you can optimise marketing strategies and allocate resources more effectively to achieve your desired outcomes.
