How can you best meet your customers in the moments that really matter; when impressions are being formed, when messaging needs to hit home, and a customer is one click away from converting?
By leveraging your data. Let’s take a look at some of the steps you can take to better inform your digital marketing strategies and yield better results from your acquisition campaigns, utilising first-party and e-commerce data.
Before switching any settings or making any campaign tweaks, take inventory of the details your business is already collecting from its consumers, across all existing touch points including your website, apps and even in-store. Using this as the foundation, assess for any data gaps or blindspots. From here, you can take steps to build out a comprehensive digital marketing strategy, from discovery through to the purchase phase.
Retail never sleeps. You can be getting ahead of the competition during ‘off-peak’ times while other brands are taking their foot off the optimisation pedal. Explore always-on solutions that can be automatically shifting, iterating, and adapting to your consumers’ behaviour. Omnichannel retail is hardly a future-facing idea, it’s the new normal so make sure your business and your customers don’t get left behind.
Keeping it simple to start is always recommended, try segmenting your consumer base into three categories: Potential Customers, New Customers, and High Value or Loyal. From here, you can tailor your content and product feeds to better speak to the specific stage a consumer is currently at in their life cycle. Then serve up sale prompts that best speak to their motivations at the most opportune times in remarketing. Tools like Google Customer Match can be really helpful for this segmentation and making the most out of your first-party data.
The most common way to use exclusion lists for e-commerce is to exclude existing or recently transacted customers from active campaigns. But you can also use exclusion lists in a similar way to how you might exclude certain keywords from a search campaign. Removing specific audiences from your marketing campaigns or ad groups that aren’t highly relevant will make ads feel more relevant and help reduce campaign costs. Whilst it might seem counterintuitive to scale down your audience, this is a case of less is more; where targeting a smaller pool of warmed up, closely aligned prospects will produce better results than speaking to a larger pool of cold, potential customers. Apply these exclusions across search, display, discovery and video campaigns.
Another way to leverage your e-commerce data to improve your digital marketing is by using an RFM model. RFM stands for: recency, frequency, and monetary. Recency refers to how much time has passed since a consumer’s last transaction with the brand. Frequency is how often a consumer has transacted or interacted with the brand during a particular time, and monetary refers to how much money a customer has spent with the brand during a certain time. You can also go one step further and divide monetary by frequency, to arrive at an average transaction amount. Applying these filters to your customer base and utilising them in your digital marketing accordingly will lead to increased customer loyalty and drive up lifetime value (or LTV).
We’re all familiar with the 80/20 rule in business and this can also apply to leveraging audience segments. Build lookalike audiences based on your best customers: those that are interacting most often with the brand and making repeat purchases. Spending too much time up at the cold end of the sales funnel can prove futile. Instead, anchor to your high lifetime value customer sets. Use them as seed audiences, and as the driving force behind your marketing campaigns.
If you’d like to better understand how to leverage your e-commerce data in your digital marketing, or further instruction on how to set up any of these particular filters or segmented audiences, speak to the team at Wondaris.
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When it comes to navigating Google Ads with new privacy, browser, and regulation changes, Google developed their Customer Match tool to help bridge the gap, enabling organisations to better leverage their 1st party data for advertising campaigns.
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