Heavy holiday sales volumes are often the key driver for success in organizations with strict attribution models and ROAS goals. So, how do you deliver programmatic success when it really counts? One particularly challenging case this holiday is the perfect example to share the four steps our team takes to build a profitable and efficient programmatic strategy. One of our e-commerce brand campaigns was reviewed under a 30% view-through attribution model, but still delivered over $16.5M in revenue. The campaign was distributed across 3 different platforms, 5 different markets, and included prospecting sales. How did we set it up:
1. Data Strategy
Building a data strategy that provides easy access points to your target audience will increase interactions with your converting audience. This allows your product or brand access to new and renewing customers. In our holiday campaign, we were able to use a 2nd Party Data buying engine that leverages retail data that constantly follows people across the web that have buying characteristics that are similar to our converting audience – allowing us to get in front of active in-market consumers. In addition, this data set was right for the timing of our campaign – all associated retailers came across the highest volume of online buyers during the holiday season (at no surprise). There a few 3rd Party audience segments that performed efficiently in this campaign such as “Holiday Shoppers” and “Electronic Purchasers”. Lastly, we were able to retarget users that have visited the landing page and used this retargeting pixel to create model audiences that “look like” users that visit and convert on site.
We also tested data that was available through Samba TV. They are able to map delivered television ads back to user devices. For example, they are able to map the group of users that were shown a TV ad to their other household devices. We were able to import this data into our buying engine and target those same users with a similar ad on their desktop, mobile, and tablet device.
With our diverse data set, we were able to test multiple segments and continue to budget around what data sets were working. A part of this diversification was including all types of data – 1st Party, 2nd Party, and 3rd Party as well as including different data partners.
2. Inventory Strategy
After you find paths to access your target audience – the next step is where to target that audience. How do you want your audience to come across your campaign and in what context? More importantly, how can we use this information to find our audience at the right place?
For our inventory selection, we used a similar overall strategy – to diversify, test, and expand spend with inventory sources based upon performance. Our plan included programmatic direct deals available through our DSP, an ecommerce targeted site list, and sites sold through 3rd Party Data partners. Our top performing tactic was our contextually targeted “Top 120 Site list” where we curated a list of all the top e-commerce websites that performed well the previous holiday season and e-commerce sites with the top retail sales after Thanksgiving and before Christmas. Our segments that we purchased through our DSP varied from consumer electronics to sites revolving around tablets and computers – the same vertical as our client.
3. Creative Strategy
Through what medium do you want your audience to understand your message and through what experience?
This needs to align with your client’s marketing objectives and if it is a lower or upper funnel messaging strategy. We used simple promotional messaging during this holiday campaign for a lower funnel marketing objective – taking into consideration the high awareness that this brand has already built. This messaging is different than other clients we have worked with in the past that use messaging as a tool to build their brand.
Will your media buying tools allow you to measure performance effectively?
If you buy media through multiple platforms – is there a way to tie performance together? If you cannot clearly measure performance, you cannot value different components of your campaign accordingly. A disadvantage of using 3 media buying platforms is the inefficiency in pulling and combining 3 data sets. If there are no resources to do this, it may make sense to deploy an ad server that will help streamline all performance and metrics.
Honing in and strategizing around these 4 components formed a strong base for our campaign. We were able to use 3 different media buying platforms, leverage new data sets, and test a group of inventory sources. Mapping all of this back to performance in our reports supported the strength of our tactics and proved strides in performance with our client’s ad dollars.