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How to Win Potential Consumers with Customer Journey Mapping on Google

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How to Win Potential Consumers with Customer Journey Mapping on Google

The author’s views are entirely his or her own (excluding the unlikely event of hypnosis) and may not always reflect the views of Moz.

If your website is like most others, there is likely a mismatch between the content you provide, and what your prospective customers search for on Google.

This article is about understanding your potential customers and their conversation with Google by using the customer journey mapping method to provide them with the best content. The idea came to me when watching internal user experience teams at our agency, and I hope it will inspire you as an SEO to leave your spreadsheets for a moment and start working with sticky notes (yeah, sticky notes).

Later in the article, as an example of the method, I will show you how a Danish insurance firm managed to come out of nowhere and dominate the conversation for a strategically important insurance product.

I have built +100 customer journey maps over the last year, so I am excited to share my knowledge with you.

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I will come back to this later, but let’s get a few definitions in place first:

What is a customer journey?

The customer journey is a model, which describes the stages a prospective customer goes through in order to convert to your solution. It is a way for us as marketers to understand what challenges a user confronts during their journey. When we understand it, we know how our marketing efforts should show up at every stage.

There are many different customer journey models, but I prefer the classic AIDA model, adding the Loyalty stage at the end.

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Here is a description of the five stages with examples of typical Google queries:

Awareness: The prospects realize that they have a problem or desire and actively start searching on Google. For example, they may think, “Hey, I’m coughing. How do I get rid of it?” and search for “How to stop coughing?” (40K monthly queries in the US).

Interest: The prospects start searching for simple solution queries. An example is “cough medicine” (59K monthly queries). In this stage, they will also look for substitutes (e.g. “honey ginger tea”).

Desire: The prospects become more educated and refine their search to find the right solution for them. They search for different attributes of the product such as segments (“infant cough medicine”) and types (“non drowsy cough medicine”). This is also the customer journey stage where users subsequently get into the buying mode with best/cheapest/discount queries (e.g. “best coughing medicine for dry cough”). They also begin to search for brands. Typical queries on Google could be “Delsym cough medicine” (5.2K monthly queries) and comparison queries, like “Delsym vs Robitussin” (1.6K monthly queries).

Action: The prospects have made their choice and are ready to take action. A typical search would be “Delsym near me” (90 monthly queries).

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Loyalty: The prospects have turned into clients and could have questions about the newly purchased product. A typical example could be “Delsym side effects”.

What is customer journey mapping on Google?

Customer journey mapping is a traditional exercise when working with user experience (UX), trying to visualize the typical touchpoints for a user and thereby understand how to create a frictionless experience.

As I mentioned in the intro, I had a light bulb moment watching our UX teams. Why couldn’t SEOs adopt this practice and map up the customer journey with Google data? Where UX teams use qualitative interviews, eye tracking, client feedback and gut feeling, Google data is the hard data that’s missing.

The idea of doing customer journey mapping on Google was born.

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We have the data right at our feet. With Google’s own data sources (e.g. Google Search Console) and third party tools (e.g. Moz Keyword Explorer), SEOs can map out a large part of the customer journey.

Just look at your user data in Google Analytics, and you will see how dominant Google is. According to a study by GrowthBadger, across industries 50-90% of all traffic came from Google. While social media is a great activation channel in 2022, prospects still go to Google when they need to educate themselves before they contact you.

By mapping the entire customer journey on Google we understand:

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  1. What are the major topics that potential clients are querying on Google?

  2. What is the search intent behind the conversation potential clients are having with Google, that might match our USPs?

  3. Where are the “peak ends”, meaning the most important conversation touchpoints on Google, that can win or lose a future customer?

  4. What is the timeline of search intent, so we understand how to prioritize content development?

Why you should use customer journey mapping on Google

There are three main arguments for why you should use customer journey mapping.

1) Targeting specific keywords is outdated. We need to focus on owning user intent instead.

Especially with Google’s introduction of BERT in September 2019, they understand searches better than ever. And with their MUM update, the search experience will become even more impressive. This also means that we, the SEOs, have to adapt to these advances, focus less on targeting specific keywords, and instead focus on the user intent.

To give an example, all the keywords below have the same intent and should be seen as one:

The total monthly search volume for this search intent is 4,000 monthly queries in the US, so this is a big touchpoint to overlook in your content, if you sell sleeping bags.

2) We need to share SEO data insights with marketing teams – and do it fast.

It should be our aim to break out of the SEO silo and ensure that SEO supports marketing strategies and activities.

People in your marketing department may not even know that Google Search Console exists, and even fewer may have access, so SEOs need to share the insights from this goldmine of data.

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SEO silo analysis can take weeks, but when aligning with the rest of the company, speed is crucial. Decisions in marketing are made on a daily basis, so SEOs need to be able to provide data quickly. A customer journey map can be created inside a few hours, and is a great way to visualize data in ways that any non-SEO can understand.

3) Topic clustering doesn’t give you the full picture.

Are you already working with topic clustering and think that customer journey mapping sounds like the same? It’s not.

A normal topic cluster only covers the Interest/Desire stages in the customer journey. A topic cluster consists of the main page (the money page), which ranks for the most important keyword (e.g. “car insurance”) and various supporting pages (pillar pages), which will rank for secondary keywords (e.g. “car insurance for teens” and “car insurance calculator”).

Customer journey mapping covers the full customer journey including the early part of the funnel and the post-sales stage. These two stages are important to pay attention to, in order to be seen as a topical authority by Google, and of course to help your prospective consumer along their entire journey.

Early-funnel

Studies have shown that helping a user early in the process will make them remember you later on. At an early stage of the journey, the prospect is not yet aware of the solution, so they will do symptom queries. This type of query isn’t so easy to identify, but this also means that your competitors are probably missing out on them. This can be a great opportunity for extra traffic.

To research symptom queries you need to think like your prospect. What would they search for when they aren’t sure what they’re looking for? A way to validate if the symptom queries are relevant for you, check in “Related searches” at the bottom of page one on Google, if any solution queries are listed. It is an indicator, if it is a relevant query or not.

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Another important aspect is to educate the prospect so they won’t choose the wrong solution. In my last Moz Blog post on SEO sprints, I showed an example of prospects searching for yellow-tinted glasses for driving at night. This is the wrong solution, because opposing cars have blue lights. This is important content to provide your audience, in order to lead prospects in the right direction. What is a misconception in your industry?

Post-sale

The post-sale queries are very valuable, because these are queries done by actual clients. This is not only about helping them out with their actual problem, but it is also an important touchpoint to warm them up for their next conversion.

If you want to identify post-sale queries quickly, then use this regex formula in your Google Search Console:

b(clean|broken|wash off|shattered|polish|problem|treat|doesn’t work|replace|doesn’t start|scratch|repair|manual|fix|protect|renew|coverage|warranty)[” “]

If you do not rank well for the queries that show up, then you most likely have a content gap.

Not all of your content will convert directly. Some content is more apt for micro conversions (see a video, read another piece of content, download pdf). With customer journey mapping, you’re forced to place the search intent in order of appearance. This will help you understand how to structure your content and what a piece of content should do.

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How to build a customer journey map using Google data

Let me walk you through the process.

Step 1 : Define your persona and your objective

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What do we want to obtain, and who is our persona/s? This important first step ensures that we create the scope for the mapping.

Step 2 : Get the data and map out the intents

Next up is to map out the user intent. I will initially use the client’s Google Search Console.

I will filter 12 months of data for a specific keyword. I will then go through my keyword list. In this example I am doing a map for “Natural playgrounds”. One intent is “natural playground equipment”. I have marked three queries below, which have the same intent: Natural playground equipment, Nature playground equipment and Nature play equipment.

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This is one intent identified. Usually, I write the intent on a sticky note with the search volume and the average ranking. Here is an example below from a session.

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When I am not able to find more intents in Google Search Console I will add data from third party tools such as Moz Explorer. Here I have inserted the keyword “Natural playground” in the suggestion box, and a list of relevant keywords appear.

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Step 3 : Map the post-its in a funnel

I then draw up a sales funnel on a whiteboard, where I place the sticky notes. I will move them around and cluster them, where it makes sense. I will eventually revisit my tools to get more data, if I see gaps in the funnel. This should be a quick process. This is how my whiteboard ends up looking:

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When I have completed this exercise I have a great understanding of the prospects’ conversation with Google. The next step is to insert the intents in PowerPoint, so it can be presented to the client. Here is an example. The traffic lights show how the site performs (Green = Rank 1-3 in Google. Yellow = Rest of page 1. Red = Page 2 or worse.). The size of the bubbles represent the search volume.

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When a map like this is presented, it will naturally kick-start a focus on how we can convert all the intents to green.

How a Danish insurance firm won prospects with customer journey mapping

Købstædernes Forsikring is one of the oldest insurance firms in Denmark, established in 1731. Historically, they have not focused on SEO, so when I started helping them, they had very little non-branded presence on Google.

Step 1 – We want to own the conversation on Google for “salary insurance”

“Salary insurance” is a product offered by all the insurance industry players. If you lose your job, then with this insurance, you can cover 90% of your salary. This is a strategically important product for Købstædernes, and Google is a big touchpoint in their prospects’ customer journey.

Step 2 – Let’s get the data for “salary insurance” and create a customer journey map

To get an understanding of potential customer search intent, we created the following customer journey map. Each bubble represents a search intent. The size of the bubble shows the relative search volume and the color represents their average ranking. I use traffic light colors to visualize this (Green: ranks in top 3, Yellow: Rank 4-10, Red: Outside page 1 on Google).

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To map out the conversation with Google, I used their Google Search Console data, supported with third party tools such as Moz Keyword Explorer. Furthermore, I held an interview with the product team to understand the potential client profiles better, so I could identify the initial symptom searches.

Since the marketing team at Købstædernes are not SEO savvy, then a customer journey map was a great way to explain that we were not part of the conversation at all. They immediately grasped our starting point, and could help by identifying the interesting conversations we should be part of. Furthermore, they could take the conversation insights and use them in the rest of their marketing mix.

Step 3 – Executing on the insights from the customer journey map

When the marketing team signed off on the journey map, we moved on to the second part, which was to understand what content to build, repurpose, and optimize. To be able to match topics between prospects’ conversation with Google and the content on the website, we needed to optimize 10 pages and create five new pages.

As with most organizations, Købstædernes does not have unlimited resources. Thus, the customer journey map was a great asset to understand how to prioritize their efforts. Content in the lower funnel should be produced first.

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Over a period of two months, my small team managed to perform these tasks. While it is not the topic of this article I would like to mention that a project management tool such as Asana, Monday.com, Trello or other is necessary to ensure an efficient process. If you use a spreadsheet (Excel, Google Sheets or other) focus on tasks can easily be forgotten. With a project management tool you can assign tasks, set deadlines, describe tasks and sub tasks, insert tags etc. I see it time and time again that when key employees leave a SEO project is put on hold. I would therefore strongly urge you to use one of these tools to avoid brain drain and focus.

The results after 10 months

Here is the development after 10 months. As you can see, we have managed to own a big chunk of the conversation:

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Traffic has gradually increased, with 100% growth for the last three months compared to the prior period.

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In summary

Google is by far the biggest touchpoint in most customer journeys across industries, so it is obvious that hard data from Google Search Console and third-party tools such as Moz Keyword Explorer can help us understand user intent. Customer journey mapping on Google is a model to enable the data by visualizing it, ensuring that the full marketing team understands the prospects’ conversation with Google.

At the same time, it gives a clear overview of content prioritization, which is an important point, since most teams have limited resources.

Let me end with a few tips about customer journey maps:

  1. Make sure you have a clear goal with your customer journey. If there is more than one goal, break the customer journey into several different customer journey maps.

  2. Understand your USPs to focus on the relevant search intent. If necessary, break down the broader user intents into smaller ones on underlying customer journey maps, to get a better overview.

I hope this blog post about customer journey mapping has inspired you to think about how you can understand your prospects’ conversation with Google in a new way. Happy mapping!

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MARKETING

Unlocking Hidden Revenue: The Inbox Retargeting Methodology

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Unlocking Hidden Revenue: The Inbox Retargeting Methodology

Page conversion rates have ALWAYS been a problem. The simple fact is most people don’t convert even on the most optimized pages. 

What’s why traditional retargeting on ad networks has been so dang powerful. While retargeted leads come cheap, they still aren’t free. Worse, you’re back competing against your competition in the ol’ ad auction system.

For the last 6 years, I’ve been using a tactic called Inbox Retargeting to identify who lands on my key pages and directly reach out to them in their inbox.

No more ads. No more auctions. Just a targeted contact that showed they were interested, but didn’t quite take the leap yet.

Before I dive into the “What’s” and “How’s”, this tactic can only be used in the good ol’ US of A. If you aren’t in the states or don’t have clients in the states, you’re out of luck. Sorry!

How It Works

Inbox retargeting doesn’t take a lot of heavy lifting. I’ll share the strategy next but I wanted to start with some of the logistics.

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DISCLAIMER: I am not a lawyer or coder, so keep that in mind if technical or legal questions pop up.

If you have a website, you have tracking scripts, e.g.,  GA4, the Facebook Pixel, Heatmap software, etc…

To get started with Inbox retargeting, you just need to be able to copy and paste two scripts on your site:

  • A collection script: This fires and tries to identify the visitor

A suppression script: You’d fire this on your conversion confirmation pages, you don’t want people who converted to land in your Inbox Retargeting campaigns.

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The tech works off of a database of contacts in the United States that are eligible for emails, so it’s completely above board with your ESP. However, you’ll want to do a few things before you start treating them like a regular member of your email list.

We initially tested this on one of our paid media campaigns. We already had a really strong campaign that we wanted to squeeze more leads out of…and boy did we.

We were driving traffic from Meta (Facebook for the OGs) to this landing page:

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This page converts at 58%. Yeah, that’s a humble brag…deal with it.

Even with a 58% conversion rate, we’re still missing out on 42% of the traffic we’ve already paid for. That’s kind of a bummer.

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After we added the collection script to the page, they were able to capture a lot more leads. The conversion rate jumped from 58% to a very sweet 87% – that’s a 50% increase!

That was the impact on a single page, that’s when we knew it was time to go bigger.

The Strategy

Most of the tools out there, whether it’s Retention.com or Customers.ai, are going to charge based on the number of contacts. So it can get pretty easy to burn through contact credits if you run the script on every page you manage, your site and your clients’ sites included.

That’s why you’ll want to make sure to select pages that capture intent versus targeting all of your traffic.

ID Key Pages

Here are some of the pages you should consider adding the collection script:

  1. Campaign Landing Pages – If you’re paying to send someone to a page, the referring source piqued their interest. If they didn’t convert, you’d definitely want to follow up.
  2. Product Pages – If someone is viewing this page they’re evaluating a particular product they were interested in.
  3. High Intent/Value Content Pages – This could be your pillar content on your blog pages, podcast pages, or your top level service pages.
  4. Registration Pages – This is a subset of a landing page, but if someone got all the way to a registration or sigh up page, they’re a prime candidate for outreach.
  5. Cart Pages – People abandon carts all the time. If you weren’t able to catch their details during checkout, this is an ideal opportunity.

Effectively it’s any page where you’re pushing a specific action. While the above pages are the pages to choose from, a homepage is acceptable but will require a little more finesse when you follow up.

Map to Email Campaigns

Now that you’ve identified where you’re going to identify leads, you’ll need to map it to your automation tool.

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Unlocking Hidden Revenue The Inbox Retargeting MethodologyUnlocking Hidden Revenue The Inbox Retargeting Methodology

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Most tools have a direct integration with your email service provider, but worst case scenario you may have to pass the data through a no code integration tool like Zapier.

Once you’ve worked out the digital plumbing, you’ll want to follow up based on the page the contact was collected on. Here’s how you should approach follow up:

  1. For Campaign Landing Pages – Give them the specific asset. They were interested in it, you’ve got their contact information, just hand over the goods. This builds good will at the start of the relationship.
  2. Product Pages – Send over the details of the product or product category they were viewing. This could be as simple as a reminder or you could build goodwill with a special offer or coupon.
  3. High Intent/Value Content Pages – Send over some of your best content or freebies that move people to the next phase of the Customer Value Journey.
  4. Registration Pages – Treat these like an “abandoned cart” type of email and get them to take that next step.
  5. Cart Pages – Same as “Registration Pages” but it’s, you know, an actual abandoned cart reminder. Similar to the product pages you could entice them to come back with a deal or coupon.
  6. Homepages – If you do run these on the homepage, you’ll need to do more of a reintroduction then transition to showcasing your best stuff.

Email Structure

The initial message you send needs to have a very specific flow. There are four critical things that need to happen when they open up your Inbox Retargeting message.

First, remind them about who you are and how they know you. This can be as simple as a, “Hey, thanks for stopping by…” message. Have some fun with it.

Next, you need to provide highly specific value based on their browsing intent. If you get this wrong, they’re just going to file your message under SPAM.

After that, you’ve got to set expectations with what they’re getting and now you’ll be communicating with them moving forward.

And Finally, you need to give them an EASY OUT. These campaigns have our highest unsubscribe rate, but that’s because we outright ask people to unsubscribe if they don’t want any additional contact.

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Once you’e gone through this, you treat them like one of your regular subscribers with all your fancy ascension automations, content emails, and promotional emails.

Here are the email stats from one of our PPC Campaigns:

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With an average open rate of 53.87%, we know there’s a base line interest in the deliverable. The click rate is DANG good for messaging visitors who didn’t convert.

Sure the unsubscribe rate is a little high for this campaign, but that is intentional. We push them to opt-out in the first email so we don’t get dinged later with complaints.

The Payoff: An Additional 109k Last Year

I mean, who doesn’t want another cool 100 grand for adding a script to your website and writing a couple of emails? Here’s how the numbers work out:

Last year, we identified 3,714 leads using this method. IMPORTANT: When I was pulling these numbers, I realized we installed the code wrong on some pages and missed out on about another 2k leads…oops!

Our average lead cost was ~$7, so the leads themself were a $26,000 additional value. This alone would be a reason to use the tech.

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BUT JUSTIN, did they convert?!

Yes!

We closed $36,000 in IPPC business from this lead source. For what we spent on those leads we’re looking at a 750% ROAS. Not too shabby.

The rest of the money we made was by selling this service to our clients. Since we run paid ads for clients, this method is a complete no brainer. We ran a pilot program and only offered this to a handful of clients last year, we averaged about 4k/month in sales.

We sold clients the leads at ~$2/lead for some of the niches we work in, that’s a steal. 

If you decide to sell this you need to make sure the client knows these are lower intent leads and will require longer term nurtures. If you follow the email strategy I shared above, you’ll be good to go!

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Protip: Charge for building the follow up sequence! 

So that’s it! If you’re running your own business or are an agency owner, you’ve got to consider Inbox Retargeting. Though, I do have some bad news…

Not to be “Chicken Little” but this is starting to get way more attention, there are services popping out of the woodwork so this will become a table stakes method. So get ahead of this today.

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What’s Media Mix Modeling? [Marketer’s Guide with Examples]

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What’s Media Mix Modeling? [Marketer’s Guide with Examples]

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By Emily Sullivan

Have you ever felt in the dark when it comes to understanding the real impact your marketing dollars are having across multiple channels? 

Determining where and how conversions are occurring is crucial in optimizing your budget to drive the most impact with your marketing budget. Media mix modeling (MMM) is an analytical approach used to gauge the effectiveness of various marketing channels in driving sales and conversions. This method allows us to decipher the true influence of advertising spend across diverse platforms by accounting for a myriad of factors, both within their control (like media channel spend, promotional strategies) and outside their control (such as economic conditions, competitor actions, and seasonal influences).

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One of the key strengths of media mix modeling is its ability to incorporate long-term brand building effects alongside immediate sales impacts, offering a comprehensive view of marketing effectiveness. It helps in identifying which channels are most efficient, how different channels influence each other, and how external factors affect marketing performance.

Media mix modeling is a powerful tool for marketers seeking to optimize their marketing investments. By providing a holistic view of how various factors contribute to sales and conversions, MMM enables data-driven decisions that enhance marketing efficiency and business growth.

In this article, we explore how media mix modeling works, and how businesses can use analytics to drive smarter ad spend decisions.

What Is Media Mix Modeling?

Media mix modeling (MMM) is a type of analysis that measures the impact of media buys across multiple channels, showing the role various elements play in achieving a desired outcome—often a conversion or revenue KPI. With this information, marketing stakeholders are able to make specific adjustments to campaign spend to improve their progress toward reaching a given goal.

Media mix modeling can be used to address common brand marketing questions and pain points, including:

  • Which of our marketing efforts are having the biggest impact on reaching our goals—or, more simply—what’s working?
  • How big of an impact does seasonality have on our marketing performance?
  • How closely is our performance tied to promotional efforts? 
  • Are shifting consumer trends negatively or positively impacting outcomes?
  • Which specific mix of spend allocation drives the highest ROI?
  • How will these channels likely perform in the future based on their optimized spend allocation?

“Media mix modeling is a top-down , privacy resilient approach that evaluates how historical media activity, promotions, pricing, seasonality, and uncontrollable factors—such as economic activity—impact key business outcomes such as sales revenue. MMM is a scientific approach to attribution in the sense that it applies statistical methods to analyze and interpret marketing data, providing a systematic understanding of how different marketing channels contribute to overall business goals in the broader context of the market. The quality of insights derived from MMM heavily depends on the quality and granularity of the data used.”

— Annica Nesty, Group Director of Marketing Science at Tinuiti

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MMM leverages aggregate data, and can measure both online (digital) and offline (traditional) advertising channel performance, including (but not limited to): paid media channels such as social media channels, traditional print advertising, linear TV advertising, and other performance marketing efforts, organic media, operational factors like promotions, external factors like seasonality, economic conditions, outcome KPIs such as sales revenue, new customers, and conversions. 

How Does Media Mix Modeling Work?

The MMM framework is a type of statistical analysis that uses statistical methods and econometric models such as a regression analysis. This econometric model helps analysts determine the strength of relationships between a single dependent variable and an array of independent variables.

Media mix modeling analysis measures the impact of your media spend today, and is also helpful in predicting the future outcome of your marketing investments on a given variable.

Example:

Let’s assume a scenario where our target metric, or dependent variable, is revenue, a critical indicator of business success. We aim to dissect the influence of various marketing initiatives on this revenue. These initiatives, our independent variables, encompass a diverse array of digital advertising campaigns, including those run on TikTok, Instagram, Snapchat, as well as broader Display and Streaming platforms.

The number of independent variables under scrutiny does not dilute our core objective. The mission is to measure the relationship between the marketing endeavors and the revenue they generate. This involves not only identifying the direct contributions of each campaign to revenue but also understanding the nuanced interplay between them by observing how changing aspects of those independent variables impacts the chosen business outcome

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What can MMM Measure?

When using MMM to assess campaign success, marketers should leverage statistical methods and econometric models to get the most accurate picture possible. Data quality is essential in achieving an accurate media mix analysis, so take any needed time to clean your data before using it in your analysis. 

Key elements an MMM equation can measure include:

  • Base and incremental sales volume impact
  • Channel effectiveness and return on investment
  • Marketing spend saturation

Media Mix Modeling vs. Data-Driven Attribution Modeling

Like media mix modeling, attribution modeling also studies the efficiency of marketing strategies — but there are important differences.

Attribution modeling is a general term that refers to tracking engagement to better understand how specific tactics drive action at the user level. This modeling works well for analyzing specific customer touchpoints, focusing on elements like how a consumer converted, which creative on which channel led to that conversion, and what the expected ROI could be if more ad budget were shifted to that channel. 

Media mix modeling takes a higher-level, more comprehensive picture. This modeling isn’t designed to measure user-level engagement like impressions and clicks, rather its primary function is measuring the impact of an entire touchpoint on specific marketing objectives. 

Data-driven attribution modeling and MMM each have their own set of strengths. It’s not a matter of one being better than the other, rather one being better-suited to different types of marketing analysis. 

For example:

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  • The precision of the data-driven attribution: Let’s assume you want to invest more spend in a social ad campaign during the holiday season. While MMM is an option for determining where to allocate those dollars, data-driven attribution excels in dissecting the intricate customer journey, offering a microscopic view of user interactions. For instance, if you’re keen on understanding the exact value of a single click from your social media campaign, Data-Driven Attribution can illuminate the path. 
  • The holistic perspective of the media mix modeling:  Media mix modeling, can consider the impact of offline actions and initiatives. Unlike the more narrowly focused attribution models, which might overemphasize the first or last touchpoint, MMM assesses the collective impact of all channels over time. This makes it an indispensable tool for strategic planning and long-term investment decisions in your marketing portfolio.

“Attribution modeling is based on a bottom-up approach while media mix modeling takes a top-down approach. Media mix modeling provides a long-term view of the marketing ROI of media activity, while attribution modeling evaluates individual-level activity to provide a short term view of marketing ROI.” 

— Annica Nesty, Group Director of Marketing Science at Tinuiti

Why Does MMM Make Sense for a Post-cookie/Post-IDFA World?

In the post-cookie and post-IDFA landscape, where privacy concerns and regulatory changes limit access to individual user-level data, media mix modeling has become a pivotal analytical tool. MMM’s emphasis on overall marketing spend allocation and its proficiency in establishing cause-and-effect models, address the challenges posed by the diminishing availability of explicit conversion information, providing marketers with a privacy-respecting and insightful approach to navigate the evolving digital advertising ecosystem.

An Example of Media Mix Modeling

With the right media mix model, a business can measure their past marketing performance to improve future ROI by optimizing the allocation of the media budget by channel and/or tactic, including: traditional and digital media channels, promotions, pricing, competitor spend, economic conditions, weather, and more.

Example:

An international ecommerce brand wanted to forecast their second-half of the year and create an optimal media mix to make their marketing dollars work smarter. A combination of client data, marketing data, and machine learning were required to create a powerful, custom media mix model. 

To build the model, the business used 2+ years of digital marketing and revenue data, analyzing it by market, tactic, and day. The data was then used to create model to assess future spend showing how changes in investment across channels could impact revenue and sales.

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media mix modeling

The full digital media mix model gave the ecommerce brand a detailed analysis of where to optimize their spend across all digital marketing channels. 

One recommendation was to shift dollars away from social—which historically had been at or near 30%—to paid search. This recommendation came with another layer of insight: The brand realized they were overinvesting in awareness campaigns, and needed to invest more heavily in capturing current demand during the 2nd half of the year.

Results: Working with a robust media mix model, the brand was able to break down how much media spend was needed by each channel in order to achieve the 30% YoY revenue goal they targeted. 

The Benefits & Challenges of Media Mix Modeling

MMM helps you accurately connect all the dots, leveraging (ideally) a wealth of provided data, to understand how disparate aspects of marketing campaigns work together in helping you reach your business goals. 

Benefits of Media Mix Modeling

The benefits of MMM are multifaceted, offering marketers a strategic edge in navigating the intricacies of their advertising efforts. Let’s dive into each benefit in detail… 

Omnichannel Campaigns: MMM excels in providing insights for omnichannel campaigns, allowing marketers to understand and optimize the impact of their initiatives across various channels. This capability is crucial in today’s interconnected digital landscape, where consumers engage with brands through diverse platforms.

Improved Oversight Over Media Spend Impact: MMM provides a comprehensive view of the impact of media spend, enabling marketers to assess the effectiveness of their investments. This improved oversight ensures a clearer understanding of how each component of the media mix contributes to overall campaign success.

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Media Spend Optimization: With MMM, marketers can optimize their media spend by identifying the most impactful channels and touchpoints. This data-driven approach allows for strategic adjustments in budget allocation, ensuring that resources are directed towards the avenues that yield the highest return on ad spend.

Effective Targeting of Audiences: MMM’s analysis helps in refining audience targeting strategies. By understanding which elements of the marketing mix resonate most with specific demographics, marketers can tailor their campaigns to effectively reach and engage their target audience segments.

Forecasting with Certainty: One of MMM’s strengths lies in its ability to forecast results with a high degree of certainty. This forecasting capability empowers marketers to make informed decisions based on predictive analytics, aiding in long-term planning and goal setting.

Reduced Reliance on Personally Identifiable Information (PII): MMM minimizes the reliance on personally identifiable information for analysis. This is especially crucial in an era where privacy concerns are more important than ever. 

Media mix modeling is a comprehensive and powerful tool, offering a range of benefits that contribute to a more effective, data-driven, and privacy-conscious approach to marketing strategy and decision-making. While there are many benefits to MMM, there are challenges as well. Let’s look into common challenges of MMM in our next section.

Challenges of Media Mix Modeling

MMM grows increasingly complex as the media landscape becomes more fragmented, and the customer journey more personalized. Whereas in the past, advertisers may have wanted to measure something as simple as the impact of a print ad in a Cleveland newspaper, today’s consumers are exposed to brands in a wide variety of locations and formats, from a subway transit poster to a Sponsored post on Instagram.

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Working with high-quality data is important in any measurement initiative, but for MMM to work effectively, it also needs a lot of data to build a reliable model. For example, if you wanted your model to consider the performance impact of seasonality, it would ideally need at least three full seasons (three years) of data to consider in its analysis.

This makes media mix modeling a ‘long game’ initiative with infrequent reporting by its nature. Brands and advertisers who are more accustomed to daily or weekly updates may struggle with ‘waiting out’ the analysis.

Because it’s not designed to make considerations based on user-level data, instead providing aggregate insights, media mix modeling offers limited insights on brand impact, personalized targeting, and customer experience. However, advanced models are available that can provide highly granular insights, but traditional MMM provides aggregate insights.

Common Misconceptions About Media Mix Modeling

Media mix modeling, like many other analytics solutions, has also become a marketing buzzword that has generated its fair share of misconceptions.

Here are a few of the most common misconceptions around media mix modeling.

Media Mix Models Are Not Transparent

With large datasets and statistical analysis involved in media mix modeling, the methods behind the technique have been critiqued for their obscurity. If there is no perceived transparency in the process, how does a brand know if its media mix model is really accurate?

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Any organization specializing in media mix modeling should provide a transparent approach, with deliverables such as outlines, milestones, and performance reports. Additionally, you may want to consider partnering with an agency that truly understands how media mix modeling aligns with your needs and expectations. Every business is unique and each media mix model is based on multiple factors.

Media Mix Models Do Not Provide Real-time Data

Today, results are often measured by the timeliness of their delivery, with the current digital marketplace allowing for almost instantaneous real-time data. Media mix models do actually provide compelling real-time marketing insights, perfect for evaluating new campaigns, new competitors, and assessing pricing actions or changes in promotional strategies. 

A powerful partner in media mix modeling will provide sophisticated tools and real-time approaches to satisfy your business performance assessments. Your partner should also be able to provide forecasting, simulation, or AI- and machine-learning-integrated models to suggest future movements. 

Media Mix Modeling is Biased to Offline Channels

Though media mix strategies do integrate and consider offline channels in their approaches, media mix modeling also considers all digital channels — including display, email, paid search, social, and more. Remember—it’s considering your media mix. If that includes ten different channels and you provide enough high-quality data for each, they will all be considered in your marketing mix analysis. 

In fact, as customers have become more intertwined with digital channels, media marketing models have adapted to go even deeper into the analyses provided by those channels’ respective insights to support better budgeting choices and customer segmentation reports. 

Conclusion: MMM Closes the Loop on Marketing Performance

In an ever-evolving digital landscape, MMM’s adaptability to the post-cookie/post-IDFA world positions it as an essential tool for marketers. As businesses seek to connect the dots, leverage data, and make strategic decisions, MMM is a crucial ally in the dynamic realm of mixed media advertising.

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“At Tinuiti, we leverage measurement best practices such as MMM and incrementality to understand media effectiveness, predict future outcomes, create deeper insights, analyzing what-if scenarios to provide recommendations that optimize media performance. This helps brands understand what channels they should be investing in, how they should shift budgets (media mix), creating a high-level view of what channels are driving overall sales and ROI. Our goal here is to deliver growth for our clients by maximizing the return on investment through best in class measurement”

— Annica Nesty, Group Director of Marketing Science at Tinuiti

At Tinuiti, we know, embrace, and utilize MMM. Our Rapid Media Mix Modeling sets a new standard in the market with its exceptional speed, precision, and transparency. 

Our proprietary measurement technology, Bliss Point by Tinuiti, allows us to measure what marketers have previously struggled to measure – the optimal level of investment to maximize impact and efficiency.  But this measurement is not just to go back and validate that we’ve done the right things. This measurement is real-time informing what needs to happen next.

Curious about how we can tailor strategies to hit your unique marketing bliss point, including Rapid Media Mix Modeling? We’re eager to chat. Contact us today for details.

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Email Ready to Send? Make Sure to Tick These Things off First!

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Email Ready to Send? Make Sure to Tick These Things off First!

Designing and developing an email campaign is a complex mechanism; a few things will inevitably escape your attention during the process. So, before you hit that send button, you must draw up a foolproof checklist to ensure every single component in your campaign is in its rightful place. Wondering what an ideal pre-flight checklist looks like? We’ve carefully compiled everything necessary in this blog. Read on to find out!

Subject Line and Pre-header Text

A subject line can make or break your emails. It’s the first thing about your email that reaches the audience, and if it fails to hit the right notes, you’ll have a tough time convincing your subscribers to engage with your emails.

What makes a subject line tick, you ask? Let’s take a look!

  • Your subject line should prioritize an economy of words; this will help you on two accounts- firstly, a crisp and to-the-point subject line increases your probability of catching the reader’s attention. Secondly, longer subject lines run the risk of being clipped on mobile devices, thereby spoiling the subscriber’s user experience. By keeping your subject lines concise, you eliminate this possibility.
  • Ensure your subject line clearly explains what readers can expect upon opening the email. The more guesswork your subject line demands of readers, the less likely they are to open your email.
  • Steer clear of using words that might be considered spammy. With email filters becoming more and more sophisticated, usage of any sort of contentious term in your subject line will result in ISPs flagging your email as spam.
  • Personalize your subject line. In a climate of increasingly crowded email boxes, personalization is one technique you simply can’t afford to overlook.

Besides fine-tuning your subject line, you also need to pay attention to your pre-header text. Building upon the context provided by your subject line, pre-header texts give readers an additional nudge to open their emails. Two crucial things that you must keep in mind while curating your pre-header texts are:

  1. It must exist only as an extension of your subject line; it must not try to introduce any new ideas on its own.
  2. It must be mobile-optimized.

Broken Links

Given that the links embedded in your email eventually facilitate a conversion, it is imperative that you thoroughly evaluate their health prior to delivering your emails. Broken links aren’t just bad for business; they also spoil a subscriber’s user experience.

Here are a few things you must check after embedding a link in your email:

  • This might sound trivial, but do check if the link you have inserted is the one you intended to or not; the only thing perhaps worse than having a broken link is having an irrelevant one.
  • Check that the link is redirecting the user to the desirable destination.
  • If the download of a resource is supposed to be triggered by clicking the link, check if that’s functioning properly; you wouldn’t want subscribers clicking umpteen times on your link only for it to return nothing.

Accessibility

Apart from acing your content and design, you must also work towards making your email campaigns accessible; people making use of assistive technologies must be able to engage with and comprehend your emails in an absolutely hassle-free manner.

Given below are a few measures that will help you make your campaigns accessible to all:

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  • Organize your email content. Break down long paragraphs into small sections of 2-3 lines. Use bullets and subheadings wherever necessary. This will make it easy for assistive technologies such as screen readers to parse through your content.
  • Write descriptive alt texts for the images you’re including. Besides improving accessibility, alt texts also enable search engines to crawl your page more efficiently, thereby boosting your SEO.
  • Use semantic markup; this will help screen readers navigate your emails in a smooth fashion.
  • Try to stick to a single-column layout while designing your email template.

This email from AllTrails is an ideal example of an accessible template.

Inbox Preview

Different email clients render emails differently, even if only slightly. Hence, before sending out your emails, you must preview them across different environments and clients to check if they appear as desired. If you are designing your email for dark mode, too, it becomes that much more important to preview it before delivering.

Wrapping It Up

For your email campaigns to be able to drive maximum impact, they must be free of blemishes of all kinds. We hope the pre-flight checklist we shared above proves to be of help to you when you sit down to create your next campaign.

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