5 Game-Changing Facts That Prove The Value Of Multi-Touch Attribution
Marketers like to try new things. One of the reasons many of us got into this profession is the ever-changing nature of it and the fact that there is always innovation: new channels, tools, tactics, and technology to learn and master.
Just in the last few years we’ve seen the growth of the marketing technology landscape to over 7,000 solutions.
But rolling out something new isn’t as easy as flipping a switch. It usually requires two things: budget approval and buy-in from the executive team.
This is especially true when launching a new marketing initiative. Let’s say you have a vision of a new campaign that you’re sure will resonate with customers. You think this could propel your organization ahead of the competition and set the stage for future growth.
The best way forward is to test your hunch before investing too much of your budget in an unproven message, channel or tactic. Running a sample campaign and measuring results will help you either prove that it worked and/or iterate to improve outcomes.
By making a direct connection between your advertising efforts and actual sales, you’ll have the proof to win over your team and get the resources you need to scale up.
In the past, marketers have relied on historical campaign data to build a case for future initiatives. This was based on traditional metrics such as clicks, using last touch attribution.
But in today’s hyper-competitive world, relying on old school metrics won’t give you the insight you need. You want to understand and prove the real impact of advertising — in dollars, not clicks.
Marketers in every industry have one question in common: “Did our marketing efforts help the company drive more revenue?” In other words, “Did our ads, emails, events, and other tactics make consumers convert?”
One way you can do this is by measuring incrementality. People use the word “incrementality” to mean different things. Strictly defined, it’s the lift that marketing and advertising provide above native demand—the increase in leads, sales or other KPI gained from marketing that would not have occurred without it.
Native demand refers to sales that happen without marketing influence. Depending on your product, there are always some people who will buy it, even if you don’t advertise. Think paper towels, light bulbs, and socks. Most of these purchases are due to native demand — a result of long-term brand awareness, basic needs, and outside factors.
A brand’s marketing efforts are designed to increase two things: the number of people aware of a product and the number of units sold. The difference between native demand and ad-driven sales represents incremental lift — the increase in sales that’s attributable to your marketing efforts.
Measuring incremental lift helps marketers understand and prove the real impact of advertising.
There have been many methods for measuring incrementality, including looking at conversions before and after your marketing efforts. But the only true way to measure causality is to use a more sophisticated approach.
Testing channels or campaigns, then comparing the sales metrics based on actual response or purchase data for two groups of your buyers—those who saw your ads and those who did not—will give you the most accurate view of the incremental sales lift.
For marketing research analysts, brand managers and channel managers, measuring lift provides powerful insights into the consumer segments and campaign elements that are driving the greatest response, so you can make smarter decisions going forward.
Testing will help you answer critical questions about the performance of your campaigns:
Once you can quantify the incremental sales impact driven by your advertising, you’ll be able to optimize your future media buys based on actual sales metrics. Most importantly, you’ll get the proof you need to end the debate over marketing value and return on advertising spend (ROAS).
Understanding incrementality allows marketers to optimize their budgets by allocating spend in the most impactful way possible. An additional benefit of measuring incrementality is that you can see which audience segments should receive increased spend and which should not.
Segments with higher incremental lift are those that need an additional “push” through the sales funnel. Those that have lower incremental lift have a greater likelihood of purchase regardless of seeing an ad. By understanding this customer journey, marketers can better optimize where they spend their dollars.
Understanding incrementality is a new way of viewing performance for those accustomed to a click-based attribution model. But when implemented correctly, incrementality can boost a brand’s revenue and help marketers prove their value.
Consumers are exposed to so many advertisements, it’s hard to know which ones they trust and act on. With Nielsen’s solution, you can make a direct connection between the media people consume and the products they buy.
Nielsen Campaign Lift uses actual credit and debit sales data, loyalty card data and/or store data to measure campaign performance. See how exposure to your advertising impacts consumer purchase behavior, including average spend, trip frequency and more, and use this insight to maximize the revenue outcome of your advertising.
When it comes to understanding how your advertising impacts purchase behavior, don’t settle for educated guesses. With Nielsen Campaign Lift, you can get the actionable intelligence you need to close the loop between advertising and sales, increase the effectiveness and efficiency of your campaigns, and make informed optimizations that generate more sales.
To learn more about how we can add value, contact one of our solutions consultants today.
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