The Biggest Thing Missing from This Year’s Oscars? A Way to Stream
by Isabel Greenfield
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Let’s wrap up the year with one of digital marketing’s most mused about topics
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If you Google the phrases ‘attribution’ and ‘digital marketing’ together, don’t be too surprised if you see the words ‘complicated’ and ‘confusing’ listed next to them in the search results. The journey is as important as the destination, as they say, and understanding the customer’s pathway on the route to conversion is as important as the sale itself. Research shows that attribution provides efficiency gains of 15-30%, and that 78% plan to increase their use of cross-channel attribution models. However, an overwhelming 77% of marketers believe that they’re either not using the right model or they don’t know which one to use.
We set the scene earlier by comparing the different types of attribution models, but what concrete best practices should one consider when approaching this widely misunderstood area of marketing? And importantly, how can marketers choose an attribution model that can accurately track Connected TV campaign performance? Read on.
We cannot stress enough the importance of adopting metrics that measure results, not channels. For example, if you’re only looking at channel-specific KPIs like Open Rates, Clicks and Impressions, then you’re only seeing performance within a vacuum and not a true picture of overall performance. This can result in making the wrong decisions when allocating budget. The ‘right’ attribution model takes the whole customer journey into account, across devices and channels, and distils that down into data that shows you how effective your campaigns are at driving the desired results. Furthermore, what makes an ideal attribution model depends on your customer buying cycles and also business goals.
MNTN recognizes the need for advertisers to employ flexibility within their attribution systems, and allows them to customize their attribution window based on their sales cycle. This is built into our proprietary Cross-Device Verified Visits model, which accurately maps the customer journey from television across their other devices, from ad impression, to site visit, to conversion. We believe that there isn’t such a thing as an ideal conversion window, because big ticket items like a car or a home is a considered purchase that will take more time and research than, say, buying groceries online. For this reason, we’ve given the power back to the advertiser to define their own conversion and attribution window directly in our user interface. Another important distinction to note is that our attribution model takes into account all devices, knowing that customers are likely to navigate between them before biting the bullet – however we won’t take credit until a viewer checks off specific criteria prior to conversion.
Did you know that customers are exposed to a brand an average of 36 times before finally making a purchase? Yep, you read that right. Additionally, over 92% of customers don’t even have an intention to buy when they first visit a brand or company’s website – they’re just browsing. This goes to show how important an accurate attribution model is to accounting for shopper behavior – and why custom attribution models like Cross-Device Verified Visits rule supreme to aim for the best accuracy.
You know what else matters when measuring attribution? Partnering with a secondary data source to ensure credibility. We have integrated the leading 3rd party data analytics platform, Google Analytics, into our reporting for an unbiased view of performance. Think of it as the ‘last stop’ in our Cross-Device Verified Visits attribution system. Any data that meets both the criteria and your chosen attribution window, will end up here. Your Connected TV advertising campaigns appear alongside any of your other digital marketing channels in GA for a holistic view of your digital strategy – making it easier for performance marketers to optimize their budgets towards the top performing channel. As we’ve noticed, MNTN has not only been driving the most qualified traffic, we’re also drawing in users that have a higher-intent to buy versus other channels. We see this in terms of time on site, increased conversion rates and session durations as the video shows.
So, we’ve explored how you can view your Connected TV campaigns against your other digital marketing practices, but what about within your actual campaigns? Investing the time into setting up your measurement and reporting efforts for attribution is well worth it, and helps you paint a picture of what is moving the needle and what isn’t. Luckily, platforms like MNTN Performance TV distil all of that data science talk into a more digestible (visual) format and helps marketers measure, view and understand performance attribution across the full funnel. Our Cross-Device Verified Visits model is fully scalable, whether you’re only running a handful of campaigns or going en masse. Simply filter the campaigns you want to see and our reporting function will automatically update for you to compare two campaigns side by side or across the board.
A study by The Drum shows that 64% of marketers agree that attribution provides insights into how their marketing channels are complementing one another (or not). We’ve looked at how to view this performance across your customer touchpoints, but where’s the baseline? Incrementality answers this important question. It also addresses whether your advertising campaign caused the consumer to convert. In simple terms, this means separating your target audience into two groups, where you serve an ad to one but not to the other. Once your campaign concludes, simply measure the difference between the two conversion rates of groups – these are your incremental conversions.
MNTN’s Performance TV Transparency report drills down to conversions on a transaction level, which displays metrics like order value next to the CTV/OTT campaign that was served, as well as what percentage of attributions your campaigns are driving across the board.
Ready to put your attribution to work, or learn more? We’re happy to show you how.