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What it is, and how it identifies vital customer touchpoints



What it is, and how it identifies vital customer touchpoints

Marketing attribution is an umbrella term describing the departments, people, and technology responsible for determining what marketing tactics and channels are contributing to sales, conversions, and leads. The responsibilities inherent in marketing attribution roles include:

  • Understanding which channels generate the most leads, sales, and revenue.
  • Identifying channels and touchpoints that refer the highest quality leads or the most valuable customers.
  • Predicting/planning marketing and/or advertising spend based on past performance.
  • Having a holistic understanding of the offline and online customer buying journey and weighting journey interactions appropriately.
  • Running/viewing reports and providing insights based on campaign data and analytics.
  • Measuring customer engagement for each touchpoint (e.g., multi-touch attribution).

In order to optimize current campaigns, and plan future ones, marketers need to know which touchpoints are effective in driving conversions. Given the complexity of today’s customer journey across digital and non-digital channels, this is an enormous challenge. The solution will have data at its core.

Marketers and C-level executives are feeling an increased demand to prove the effectiveness of their ad campaigns and marketing initiatives. For instance, 59% of marketing leaders said they face high levels of pressure from CEOs to show the impact of their efforts, according to the August 2021 CMO Survey sponsored by the American Marketing Association, Deloitte, and Duke University’s Fuqua School of Business. Marketing attribution has the potential to address this need.

In this post, we’ll cover the basics of marketing attribution — what it is, why it’s important, and how marketing and sales teams can succeed with it. Key points covered include:

Estimated reading time: 11 minutes

What is marketing attribution?

Marketing attribution is the process of measuring and assigning credit to any channel or touchpoint that impacts a company’s pipeline and revenue. However, the problem with attribution is that both B2B and B2C customer journeys are becoming more complex.

Traditional attribution modeling relies on interpreting static ROI metrics in a dynamic marketing environment. This can lead to false assumptions — and incorrect attribution — if marketers fail to dig deeper.

A dynamic marketing environment refers to the nonlinear characteristic of the modern customer journey. It speaks to how each piece of content, interaction, and experience contributes to the culmination of the buying journey (e.g., the sale, lead, or conversion).

Tracking and measuring interactions is the easy part. Understanding the context and importance of each interaction—how it ultimately contributes to the customer’s final action — is the hard part, particularly when you’re weighing the combined impact of offline and online channels. The ability to do this well begins and ends with data, so it makes sense that the tools that facilitate marketing attribution focus on ingesting, measuring, and interpreting data.

Types of marketing attribution models

There are several different types of marketing attribution models that marketers use to assign credit to their initiatives. It’s important to understand them if you want to do marketing attribution the right way.

First-touch attribution. This model gives 100% of the credit for a conversion or sale to the first customer touchpoint. Take paid search or social clicks, for example. It’s very easy to give a paid search or social ad all the credit for a sale because it’s easy to see the click-to-sale funnel in your Google Analytics report.

But this model also relies on third-party cookies to deliver the information. (We’ll get to why that’s a problem in a bit.) It also discounts any other interactions the customer may have had before or between the ad click and the final sale. This is the model that tends to annoy your sales team since the credit is given to the channel bringing in the lead rather than the work required to close the sale.

Last-touch attribution. This gives 100% of the credit for a conversion or sale to the last touchpoint the customer interacted with before converting. Sales teams like this model because it tends to favor sales materials like eBooks, webinars, and demos over top-of-funnel touchpoints like search ads.

Multi-touch attribution. Multi-touch gives credit to every touchpoint and interaction along a customer’s buying journey that contributes to the final conversion or sale. Traditional multi-touch models tend to be linear, meaning they weigh each touchpoint equally. There’s been much debate about the value of making assumptions based on metrics alone (e.g., more leads equals more success).

In a perfect multi-touch attribution world, marketers can weigh the impact of each touchpoint based on how it influences the final sale or conversion. This is where martech tools can help.

Explore capabilities from vendors like Adobe, Pointillist, SharpSpring, Salesforce and more in the full MarTech Intelligence Report on customer journey analytics platforms.

Click here to download!

Why should marketers care about attribution?

The only way marketers can optimize current and future campaigns is by knowing which touchpoints are effective in driving results. Given the complexity of today’s customer journey across digital and non-digital channels, this is an enormous challenge.

That some marketing dollars will inevitably be wasted is not news. Way back in 2018, nearly 30% of global marketers said they wasted nearly a third of their marketing budgets, and half wasted about 20%.

Marketing attribution promises to redirect the flow of wasted dollars from ineffective channels to those channels and tactics that are most effective. When it comes to marketing, everything is measurable.

You should care about proper marketing attribution because:

  • It tells you what things you should be paying attention to and which have less value.
  • It helps you predict what’s coming so you can make real-time adjustments in your marketing approach.
  • It helps you spend your marketing dollars wisely.
  • It empowers your marketing and sales teams to make better decisions about their budgets and time.
  • It requires that marketing, sales, product, and management teams talk to each other to evaluate the customer journey holistically.
  • It banishes data siloes.

However, marketing attribution isn’t a perfect science. Markets are “complex adaptive systems,” says marketing strategist Kathleen Schaub, meaning the interactions between audiences and brands can be unpredictable with so many factors creating feedback loops. Marketers must acknowledge that ROI measurement is complex and requires a combination of optimized management structures and high-quality marketing attribution tools.

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While every team in an organization benefits when they understand their company’s unique buying cycle, marketing attribution tools are generally the purview of marketing teams.

Here are some use cases that highlight these tools and how they’re used.

The CMO of a B2B company wants to understand how the latest top-of-funnel brand strategy is impacting revenue. Connecting branding initiatives to revenue is a tough exercise. It requires measuring things like brand experience and level of awareness based on interaction and engagement, ultimately tying both to sales. Tools like SproutSocial and Brandwatch can be integrated with marketing analytics platforms to understand how marketing impacts brand awareness, which impacts sales.

The CMO of a global retail chain wants to understand what paid media channels contribute to the highest-value customers. Multi-touch attribution can help this CMO understand which paid media sources deliver the highest value customers by tying the top-of-funnel tactic (e.g., search ads) to mid- and low-funnel activities (e.g., adding items to the shopping cart, initiating a chat on the e-commerce website, etc.) The goal here is to redistribute ad spend to the most effective activities without increasing the marketing budget.

The owner of a local restaurant wants to know what offers and promotions resonate best with customers. Consumer behavior data procurement is vital when making marketing decisions, and marketers need attribution tools to help identify which events in the buyer journey drive the most conversions. Attributing conversion values to specific offers, promotions, and other calls-to-action can show businesses which circumstances lead to higher levels of customer buy-in.

The CEO of a Fortune 500 tech company wants to move away from third-party data and better understand the buying journey from their customers’ perspective. Appropriate attribution requires high-quality data, but most marketers currently use third-party cookies to create, track, and optimize ad campaigns. As we move to a cookieless world, marketing attribution will increasingly rely on first-party data using tools like CDPs, identity resolution platforms, and journey orchestration engines (JOEs) to get a deep understanding of their customers’ buying journey.

Looking to take control of your data? Learn about trends and capabilities of customer data platforms in the latest edition of this MarTech Intelligence Report.

Click here to download!

The CMO of a CPG brand wants to understand if pairing certain online and offline touchpoints lift brand and/or ad recall. Marketing attribution, if done right, will enable you to unify every channel and touchpoint across the buying journey. Machine learning and AI can make these connections for you, synthesizing data from a range of sources to surface insights that can help you understand how offline touchpoints like TV and radio work with digital channels to improve campaign performance.

Any tool that helps identify how your ads, content, and media contribute to campaign performance falls under the umbrella of marketing attribution software. But to be considered a true marketing attribution platform, a tool must contain the following features:

  • It supports a broad range of online and offline channels: digital, TV, radio, OTT, podcast, and IoT to capture interactions between your customers and your brand.
  • It offers “big picture” analysis by ingesting — and normalizing — data from a variety of campaigns, platforms, and sources.
  • It supports statistical modeling to get more meaningful information from incomplete or imperfect data.
  • It employs predictive analytics generally via AI and machine learning to help marketers plan campaigns.
  • It uses a variety of different attribution models, including single-touch, multi-touch, algorithmic, custom models, etc. to support all business types.
  • It has robust reporting and data visualization features that can deliver insights and reports in real-time based on user-specific KPIs and goals.
  • It integrates with martech/ad tech tools, e.g., fits seamlessly with your tech stack.
  • It typically has a relationship with walled-garden platforms like Amazon and Facebook to add additional data points that yield deeper insights.

Examples of marketing attribution tool capabilities

Marketers looking for tools that give them more in-depth customer touchpoint data will find a slew of helpful functions in attribution tools. Here are some of their capabilities and offerings.

Ingestion and management of offline marketing data. Although more and more marketing touchpoints are moving to digital channels, offline events still account for a large portion of most customer journeys and continue to grow. Attribution tools can help marketing account for this offline data to ensure these touchpoints don’t get lost in the mix.

A single source of truth when evaluating channel effectiveness. Since marketing attribution tools measure touchpoints from a variety of channels and platforms, they’re able to offer marketers a single source of baseline data, which helps increase their confidence in the numbers.

Increased opportunities for personalization. Attribution tools can give marketers a more accurate picture of their customers’ preferred communication mediums and channels. This valuable data makes it easier for marketers to increase personalization.

Campaign spend analysis. These tools do a great job of offering marketers insights into the channels and touchpoints that have the best ROI. This allows them to better allocate campaign spend to the most profitable areas.

Each attribution platform is different, so remember to ask vendors about their specific capabilities when evaluating your options.

How marketing attribution can help marketers succeed

Marketing attribution technology can help marketers justify budgets and plan more effective strategies without third-party cookies. Unifying customer journey data across touchpoints and channels can help marketing and sales teams deliver more value.

Marketers are beginning to understand what consumers already knew — it’s all one buying journey. According to a recent study by The Trade Desk, the number of marketers who plan to use sales data very frequently will triple in the coming year. In addition, nearly 80% of respondents said they plan to use point-of-sale data to inform their advertising activity, connecting this activity to consumer purchases that occur both in physical stores and online.

While marketing attribution relies on good data, it also requires knowledge of the current market and a multi-disciplinary approach to analyzing — and acting on — campaign performance data. Marketers who connect the dots across the entire buying journey are in a much better position to anticipate and respond to changes in the market (and in consumer behavior) than those who don’t.

Resources for learning more about marketing attribution

There are many tools and resources available that can help brands track and gain insights from each customer touchpoint. Here are some we believe will be beneficial:

Marketing attribution and predictive analytics: A snapshot

What it is. Marketing attribution and predictive analytics platforms are software that employ sophisticated statistical modeling and machine learning to evaluate the impact of each marketing touch a buyer encounters along a purchase journey across all channels, with the goal of helping marketers allocate future spending. Platforms with predictive analytics capabilities also use data, statistical algorithms and machine learning to predict future outcomes based on historical data and scenario building.

Why it’s hot today. Many marketers know roughly half their media spend is wasted, but few are aware of which half that is. And with tight budgets due to the economic uncertainty brought about by the COVID-19 pandemic, companies are seeking to rid themselves of waste.

Attribution challenges. Buyers are using more channels and devices in their purchase journeys than ever before. The lack of attributive modeling and analytics makes it even more difficult to help them along the way.

Marketers continuing to use traditional channels find this challenge magnified. The advent of digital privacy regulations has also led to the disappearance of third-party cookies, one of marketers’ most useful data sources.

Marketing attribution and predictive analytics platforms can help marketers tackle these challenges. They give professionals more information about their buyers and help them get a better handle on the issue of budget waste.

Read Next: What do marketing attribution and predictive analytics tools do?

About The Author

Jacqueline Dooley is a freelance B2B content writer and journalist covering martech industry news and trends. Since 2018, she’s worked with B2B-focused agencies, publications, and direct clients to create articles, blog posts, whitepapers, and eBooks. Prior to that, Dooley founded Twelve Thousand, LLC where she worked with clients to create, manage, and optimize paid search and social campaigns.

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45 Free Content Writing Tools to Love [for Writing, Editing & Content Creation]



45 Free Content Writing Tools to Love [for Writing, Editing & Content Creation]

Creating content isn’t always a walk in the park. (In fact, it can sometimes feel more like trying to swim against the current.)

While other parts of business and marketing are becoming increasingly automated, content creation is still a very manual job. (more…)

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How data clean rooms might help keep the internet open



How data clean rooms might help keep the internet open

Are data clean rooms the solution to what IAB CEO David Cohen has called the “slow-motion train wreck” of addressability? Voices at the IAB will tell you that they have a big role to play.

“The issue with addressability is that once cookies go away, and with the loss of identifiers, about 80% of the addressable market will become unknown audiences which is why there is a need for privacy-centric consent and a better consent-value exchange,” said Jeffrey Bustos, VP, measurement, addressability and data at the IAB.

“Everyone’s talking about first-party data, and it is very valuable,” he explained, “but most publishers who don’t have sign-on, they have about 3 to 10% of their readership’s first-party data.” First-party data, from the perspective of advertisers who want to reach relevant and audiences, and publishers who want to offer valuable inventory, just isn’t enough.

Why we care. Two years ago, who was talking about data clean rooms? The surge of interest is recent and significant, according to the IAB. DCRs have the potential, at least, to keep brands in touch with their audiences on the open internet; to maintain viability for publishers’ inventories; and to provide sophisticated measurement capabilities.

How data clean rooms can help. DCRs are a type of privacy-enhancing technology that allows data owners (including brands and publishers) to share customer first-party data in a privacy-compliant way. Clean rooms are secure spaces where first-party data from a number of sources can be resolved to the same customer’s profile while that profile remains anonymized.

In other words, a DCR is a kind of Switzerland — a space where a truce is called on competition while first-party data is enriched without compromising privacy.

“The value of a data clean room is that a publisher is able to collaborate with a brand across both their data sources and the brand is able to understand audience behavior,” said Bestos. For example, a brand selling eye-glasses might know nothing about their customers except basic transactional data — and that they wear glasses. Matching profiles with a publisher’s behavioral data provides enrichment.

“If you’re able to understand behavioral context, you’re able to understand what your customers are reading, what they’re interested in, what their hobbies are,” said Bustos. Armed with those insights, a brand has a better idea of what kind of content they want to advertise against.

The publisher does need to have a certain level of first-party data for the matching to take place, even if it doesn’t have a universal requirement for sign-ins like The New York Times. A publisher may be able to match only a small percentage of the eye-glass vendor’s customers, but if they like reading the sports and arts sections, at least that gives some directional guidance as to what audience the vendor should target.

Dig deeper: Why we care about data clean rooms

What counts as good matching? In its “State of Data 2023” report, which focuses almost exclusively on data clean rooms, concern is expressed that DCR efficacy might be threatened by poor match rates. Average match rates hover around 50% (less for some types of DCR).

Bustos is keen to put this into context. “When you are matching data from a cookie perspective, match rates are usually about 70-ish percent,” he said, so 50% isn’t terrible, although there’s room for improvement.

One obstacle is a persistent lack of interoperability between identity solutions — although it does exist; LiveRamp’s RampID is interoperable, for example, with The Trade Desk’s UID2.

Nevertheless, said Bustos, “it’s incredibly difficult for publishers. They have a bunch of identity pixels firing for all these different things. You don’t know which identity provider to use. Definitely a long road ahead to make sure there’s interoperability.”

Maintaining an open internet. If DCRs can contribute to solving the addressability problem they will also contribute to the challenge of keeping the internet open. Walled gardens like Facebook do have rich troves of first-party and behavioral data; brands can access those audiences, but with very limited visibility into them.

“The reason CTV is a really valuable proposition for advertisers is that you are able to identify the user 1:1 which is really powerful,” Bustos said. “Your standard news or editorial publisher doesn’t have that. I mean, the New York Times has moved to that and it’s been incredibly successful for them.” In order to compete with the walled gardens and streaming services, publishers need to offer some degree of addressability — and without relying on cookies.

But DCRs are a heavy lift. Data maturity is an important qualification for getting the most out of a DCR. The IAB report shows that, of the brands evaluating or using DCRs, over 70% have other data-related technologies like CDPs and DMPs.

“If you want a data clean room,” Bustos explained, “there are a lot of other technological solutions you have to have in place before. You need to make sure you have strong data assets.” He also recommends starting out by asking what you want to achieve, not what technology would be nice to have. “The first question is, what do you want to accomplish? You may not need a DCR. ‘I want to do this,’ then see what tools would get you to that.”

Understand also that implementation is going to require talent. “It is a demanding project in terms of the set-up,” said Bustos, “and there’s been significant growth in consulting companies and agencies helping set up these data clean rooms. You do need a lot of people, so it’s more efficient to hire outside help for the set up, and then just have a maintenance crew in-house.”

Underuse of measurement capabilities. One key finding in the IAB’s research is that DCR users are exploiting the audience matching capabilities much more than realizing the potential for measurement and attribution. “You need very strong data scientists and engineers to build advanced models,” Bustos said.

“A lot of brands that look into this say, ‘I want to be able to do a predictive analysis of my high lifetime value customers that are going to buy in the next 90 days.’ Or ‘I want to be able to measure which channels are driving the most incremental lift.’ It’s very complex analyses they want to do; but they don’t really have a reason as to why. What is the point? Understand your outcome and develop a sequential data strategy.”

Trying to understand incremental lift from your marketing can take a long time, he warned. “But you can easily do a reach and frequency and overlap analysis.” That will identify wasted investment in channels and as a by-product suggest where incremental lift is occurring. “There’s a need for companies to know what they want, identify what the outcome is, and then there are steps that are going to get you there. That’s also going to help to prove out ROI.”

Dig deeper: Failure to get the most out of data clean rooms is costing marketers money

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Ascend | DigitalMarketer



Ascend | DigitalMarketer

At this stage, your goal is to generate repeat buys and real profits. While your entry-point offer was designed for conversions, your ascension offers should be geared for profits—because if you’re serving your customers well, they’ll want to buy again and again.

Ascension offers may be simple upsells made after that initial purchase… bigger, better solutions… or “done for you” add-ons.

So now we must ask ourselves, what is our core flagship offer and how do we continue to deliver value after the first sale is made? What is the thing that we are selling? 

How we continue to deliver value after the first sale is really important, because having upsells and cross sales gives you the ability to sell to customers you already have. It will give you higher Average Customer values, which is going to give you higher margins. Which means you can spend more to acquire new customers. 

Why does this matter? It matters because of this universal law of marketing and customer acquisition, he or she who is able and willing to spend the most to acquire a customer wins.

Very often the business with the best product messaging very often is the business that can throw the most into customer acquisition. Now there are two ways to do that.

The first way is to just raise a lot of money. The problem is if you have a lot of money, that doesn’t last forever. At some point you need economics. 

The second way, and the most timeless and predictable approach, is to simply have the highest value customers of anyone in your market. If your customers are worth more to you than they are to your competitors, you can spend more to acquire them at the same margin. 

If a customer is worth twice as much to you than it is to your competitor, you can spend twice as much trying to acquire them to make the same margin. You can invest in your customer acquisition, because your customers are investing in your business. You can invest in your customer experiences, and when we invest more into the customer we build brands that have greater value. Meaning, people are more likely to choose you over someone else, which can actually lower acquisition costs. 

Happy customers refer others to us, which is called zero dollar customer acquisition, and generally just ensures you’re making a bigger impact. You can invest more in the customer experience and customer acquisition process if you don’t have high margins. 

If you deliver a preview experience, you can utilize revenue maximizers like up sells, cross sales, and bundles. These are things that would follow up the initial sale or are combined with the initial sale to increase the Average Customer Value.

The best example of an immediate upsell is the classic McDonalds, “would you like fries with that?” You got just a burger, do you also want fries with that? 

What distinguishes an upsell from other types of follow up offers is the upsell promise, the same end result for a bigger and better end result. 

What’s your desired result when you go to McDonalds? It’s not to eat healthy food, and it’s not even to eat a small amount of food. When you go to McDonalds your job is to have a tasty, greasy, predictable inexpensive meal. No one is going there because it’s healthy, you’re going there because you want to eat good. 

It’s predictable. It’s not going to break the bank for a hamburger, neither will adding fries or a Coke. It’s the same experience, but it’s BIGGER and BETTER. 

Amazon does this all of the time with their “Customers Who Bought This Also Bought …” But this one is algorithmic. The point of a cross sell is that it is relevant to the consumer, but it doesn’t necessarily have to be aligned with the original purchase. What you don’t want to do is start someone down one path and confuse them.

You can make this process easy with Bundles and Kits. With a bundle or a kit you’re essentially saying to someone, “you can buy just one piece, or you can get this bundle that does all of these other things for a little bit more. And it’s a higher value.”

The idea behind bundles and kits is that we are adding to the primary offer, not offering them something different. We’re simply promising to get them this desired result in higher definition. 

The Elements of High-Converting Revenue Maximizers (like our bundles and kits) are:

  1. Speed

If you’re an e-Commerce business, selling a physical product, this can look like: offering free shipping for orders $X or more. We’re looking to get your customers the same desired result, but with less work for them.

  1. Automation

If you’re a furniture business, and you want to add a Revenue Maximizer, this can look like: Right now for an extra $X our highly trained employees will come and put this together for you. 

  1. Access 

People will pay for speed, they’ll pay for less work, but they will also pay for a look behind the curtain. Think about the people who pay for Backstage Passes. Your customers will pay for a VIP experience just so they can kind of see how everything works. 

Remember, the ascension stage doesn’t have to stop. Once you have a customer, you should do your best to make them a customer for life. You should continue serving them. Continue asking them, “what needs are we still not meeting” and seek to meet those needs. 

It is your job as a marketer to seek out to discover these needs, to bring these back to the product team, because that’s what’s going to enable you to fully maximize the average customer value. Which is going to enable you to have a whole lot more to spend to acquire those customers and make your job a whole lot easier. 

Now that you understand the importance of the ascend stage, let’s apply it to our examples.

Hazel & Hem could have free priority shipping over $150, a “Boutique Points” reward program with exclusive “double point” days to encourage spending, and an exclusive “Stylist Package” that includes a full outfit custom selected for the customer. 

Cyrus & Clark can retain current clients by offering an annual strategic plan, “Done for You” Marketing services that execute on the strategic plan, and the top tier would allow customers to be the exclusive company that Cyrus & Clark services in specific geographical territories.

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