Eliminating Wasted Ad Spend With Accurate Attribution Modeling

Eliminating Wasted Ad Spend With Accurate Attribution Modeling

Attribution modeling is quickly becoming an essential tool and skillset for marketers. Without attribution, marketers can only look at ad impressions and clicks to make decisions on optimizations, says AJ Brown, CEO, and Co-founder of LeadsRx

Accurate attribution is one of the most significant issues that marketers face today; how can this be resolved?

Accuracy starts with making sure you’re looking across as many marketing channels that you can. Stay away from attribution point-solutions that only attribute a single channel – these don’t tell the whole story and lead to incomplete and, therefore, inaccurate studies. Accurate attribution needs to look at all marketing channels together and evaluate all touch points where prospects are developing trust with a brand. Look for impartial multi-touch attribution tools that don’t have a bias towards any specific medium.

From a data collection standpoint, accuracy requires a pixel that isn’t limited by ever-restrictive cookie technologies. All attribution begins with monitoring a customer’s journey as they come in contact with marketing programs, your website, and other business assets – both online and off. Cookies are an intimate part of this process, but some attribution tools rely on third-party and first-party cookies that either already don’t work or that are on the chopping block as browsers respond to privacy concerns.  Look for a “universal pixel” that uses the most rigorous cookie placement policies and accurately tracks 100% of the customer journey. If the tracking pixel isn’t present in a significant portion of conversions, your attribution results are not going to be accurate – so make sure you are using tracking technology that is resilient and universal.

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How crucial is it for marketers to get accurate insights based on full-funnel Return on Ad Spend (ROAS) analysis across touch points of every customer conversion?

A Return on Ad Spend analysis is critical to really understand marketing program impact. In an extreme example, imagine you spend 10x more money on Facebook than Google. Chances are, you’re going to see a more significant number of conversions influenced by Facebook. But the numbers are swayed by the investment. If you instead look at ROAS, numeric counts are normalized to dollars and cents, and the comparison is made to revenue, not counts of conversions. As a result, you can clearly see which channel is the most cost-efficient, which produces the highest-paying customers, and how all channels contribute to success in a dollars-to-dollars comparison. Ad-spend optimizations can only be made accurately when looking at ad-spend reporting.

Do you agree that firms face marketing failures because they do not focus enough on customer journey mapping and performance tracking in real-time?

“Failure” is a strong word, but certainly without journey mapping and performance tracking, marketers sometimes introduce bias into their analysis and suffer from wasted ad spend. For example, they may favor Google Ads simply because they see a lot of ad clicks or are more familiar with that platform. We’d all like to think our experience and “gut instinct” is part of our personal skill set. Still, the reality is marketers who rely on analytic evidence ultimately go further in their careers and have more productive relationships with their peers and supervisors. Click-counting and building on what worked “last time” may not cause a marketer or their efforts to be labeled as a “failure.” But, developing accurate customer journey mapping and analytics as core competencies will bring success both professionally and in terms of maximizing ROAS.

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How can firms eliminate their wasted ad spend?

Eliminating wasted ad spend starts with accurate attribution modeling, ROAS reporting, and removing personal bias from decisions. Then, it’s genuinely a matter of just looking at the data, and, most importantly, taking action. This step is often overlooked, and it’s surprising. Any marketing analytics package is only worth the cost if marketers take action based on the insights they get. A ROAS report will clearly show ad spend that could be classified as “wasted,” but some people struggle with implementing changes because of internal politics, lack of time, or a fear of change. Eliminating wasted ad spend requires immediate action to stop programs that don’t have a ROAS higher than the amount of spend (i.e., a ROAS value better than 1x).  Monitor this value over a date range acceptable for your particular business and make the change.

How important is it for marketers to invest in attribution software? What is the biggest obstacle stopping them from investing in such attribution software?

I think there’s a perception that marketing attribution platforms are expensive – and they used to be. About five years ago, solutions in the marketplace were costing $10k/month and up. But today, there are multiple solutions available at around $500/month to accommodate all sizes of marketing budgets. Another obstacle has been a perception that getting set up with attribution takes months of dedicated time. Again, this is no longer true with several self-service SaaS solutions now available, making attribution something any marketer can set up in just a couple of days. Attribution modeling is quickly becoming an essential tool and skillset for marketers. Without attribution, marketers can only look at ad impressions and clicks to make decisions on optimizations. But with 98% of ad clicks failing to deliver actual customers, this approach leads to significant errors. Attribution focuses on the other 2% of the ad clickers who actually convert to become buyers. This is the audience every marketer wants to increase in size and value, and attribution is the marketing methodology designed to make that happen.

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AJ Brown is CEO and co-founder of LeadsRx, a marketing attribution technology company. AJ provided the initial inspiration for LeadsRx, having been head of marketing for several businesses over his career as well as head of software engineering. He has 25 years of experience working with established companies as well as fast-paced Silicon Valley startups, helping build traction and delivering high-impact lead generation programs.