There’s so much data, from so many different sources, with so many different reporting tools, that you could just drown in reports, attribution, and meetings. With so much noise out there, it’s important that you look at the data in a certain way. There’s important information hidden in the metrics that will help direct your digital marketing strategy.
In this article I’m going to walk you through this technique that I’ve been using for 25 years, called MAA.
Metrics, Analysis, Action
MAA stands for metrics, analysis, action.
Let me show you how powerful it is when you use this technique on any kind of data set you have. It could be SEO data, website data, email data, conversion data, shopping cart data.
The Data Doc is in…
Think of this as if you are a surgeon in the emergency room. You must follow these three steps.
- Collect vitals.
First you collect the vitals. It could be heart rate, blood pressure, respiratory rate, x-rays things like that. These are the numbers that clue you in to the cause of the problem.
The second phase is the diagnosis. In this phase you interpret all the vitals that you collected. Based on the data, you make the determination of a heart attack, broken bone, virus, etc. The key point is that the diagnosis is based on the data.
From that diagnosis, you create the treatment plan. The plan might include surgery, medications, a recovery plan, etc. But the list of things to be done to make the patient healthier is based upon the findings and the diagnosis.
The marketing analytics data you collect leads directly to analysis of the problem. That then leads directly to the action. What I will show you in this article is a number of examples from a variety of digital marketing projects. This works whether you’re working on a large or small project.
Data vs Analytics
Lots of people think that they have analytics because they have Google Analytics installed on their website.
But let me tell you a dirty secret.
There are no analytics in Google Analytics. It’s just Google charts. It should be called Google Chart-Maker.
Marketing analytics is figuring out what’s actually going on. It’s the interpretation of the data. Interpreting the data tells you why sales went up or down. It helps you discover why conversion rates went up or down. Analyzing the data answers questions like:
- Why did people buy or not buy?
- Why did a competitor take a certain action?
- Where are we losing customers along the customer journey?
- Is our content hitting or missing with our customers?
Analytics is more than making charts and collecting data. And action is the next step after marketing analytics.
The way we see it, if you are not taking action based on the analytics, which was based on the data, then whatever you’re doing is random.
Returning to our analogy, not everyone should take the same pill. If you’ve got a broken bone, you shouldn’t take the same medication as someone who has a headache. So the action that you take, the optimization, should be contingent upon the analysis, which should go straight back to the data that you gathered.
Most people make the mistake of just trying to look at lots of data. This Metrics Analysis Action framework is the easiest way to figure out what you really need to do versus what’s noisy.
MAA Framework Case Study: Ecommerce
If you are in ecommerce, lead gen, or any kind of performance marketing, then you’re going to start with the action, mapped back to the analysis, and back to the metrics.
Because the actions are all the things that you could do.
So make a list of the things that you could do.
- You can play with the website.
- You can change your budgets.
- You can change ads.
- You can optimize creatives.
- You can work with influencers.
- You can buy another tool.
- You can change bids.
Think of all the actions that you could take. Start with the end in mind.
Once you decide on the action, look for the trigger. In other words, when analyzing the data, what diagnosis will cause you to take that prescribed action?
That’s where you have automated rules on Google, Facebook, or Shopify. Wherever you’re looking at data, you can set up these rules.
For example, if your cost per acquisition goes above $50, then turn the ad set off. If someone leaves a positive review on Yelp, then reach out to them to say thank you.
So if a certain thing happens, then here’s the particular action.
Then there’s a limited number of things that you could do, so you don’t have to look at everything. And then if you need to determine if that triggering condition is true, then what data do you need?
Data, Analytics, and Attribution
On the far left of this image, we have plumbing. Plumbing is collecting the data from different tags in tag manager, UTM parameters, pixels that are firing, and other events inside an app.
These are the things that people are doing. For example, opening an email. When that happens, you get plenty of email marketing data. But the data doesn’t mean anything unless you can tie it to a goal.
How do you tie data to a goal?
Here’s a lifetime value example…
Seeds of Life sells flowers to people who’ve experienced the death of a loved one. The lifetime value (LTV) of a customer is $150. What can they do to increase the LTV?
They might offer a referral bonus, free shipping for orders over a hundred dollars, etc. Their goals, checked against the marketing analytics, will determine the direction of their next marketing campaign.
The important thing is to define the goals and measure them against the data. If the data doesn’t tie to the achievement of a particular goal, then you have to ask, “why are we even collecting that data?”
We’re not searching for a needle in a haystack, here. Although, that’s what most people do with their reporting.
Most people log into Google analytics, or whatever they use to pull in all the data from all the different places. And then they just hunt and peck and wander around and look for interesting things.
They look at the data then filter down to this date for that particular segment and this part of the country. It’s like the lotto, like the power ball where you choose six random balls to try to win the million dollar jackpot.
You want to have your goals before you figure out the plumbing.
Don’t Make the Same Mistakes with Analytics
Large and small companies make the same mistakes. They tend to go after impressions or click through rate or secondary metrics when the primary metric, the business goal, is more important than a diagnostic, secondary metric.
I love looking at cost per mille, or CPM, in advertising. For example, how much are you paying per thousand impressions? What is the trigger or check engine light, to let you know whether the algorithm is penalizing you for having a low click through rate, low quality score, low relevance score, etc.
Analyzing a marketing campaign in this way may show that something else is wrong.
Please don’t make the same mistake thinking that a secondary metric like click through rate, cost per click, quality score, or CPM is more important than the main business metric.
Profit, lifetime value, or cost of acquisition should be the goals that tie to your content and targeting.
Plumbing, Goals, Content, Targeting, Amplification, Optimization…
Here’s an example (above) of a marketing campaign we ran for our friend, Brennan.
At the very top are the financial metrics, specifically profit. There’s some kind of margin with or without cost of goods and services or overhead.
Then we have revenue minus costs.
Revenue is driven by factors like conversion rate, LTV, and how well you use things like recency and frequency to increase revenue.
Then there’s costs: people costs, ad costs, software costs, other kinds of costs.
On the revenue side, units (high price vs low price) multiplied by volume (clicks and/or conversion rate) is your revenue.
On the cost side, let’s say you run all your digital marketing campaigns on a cost per click basis. You can break that down to different fixed and variable costs. So we know if we double the number of clicks we’re buying from Google, we’re going to pay twice as much. Multiply the cost by the number of clicks you get for the overall cost of that campaign.
This decomposition pyramid helps you figure out the data you need to collect using secondary diagnostic metrics.
Start to think about how those different metrics will help you uncover the main issue to focus on right now.
MAA Framework: Case Study
Let’s look at how this actually applies when you’re looking at tabular data.
In this example (above), we’re looking at a lot of information. There are 132 ad sets here. That means we have all this information for 132 projects…
- Landing pages
This happens to be a set of Facebook campaigns, but it could easily be any social media platform or other traffic source.
We use a concept called “Top N” to select a manageable number of ad sets to work with. Why? Because it’s intimidating to try and look at ALL of them to diagnose the problem or issue.
You don’t have time to look at every single keyword, creative, or landing page. The idea of Top N is to look at the top, best- or worst-performing ad sets and ignore the rest. This is just another way of using the 80/20 rule or prioritizing your work.
I find that when you use the Top N technique on any large dataset you can quickly zero in on the most important thing.
In this case, we can see that this very first ad spent $10,000 out of $43,000. That means 25% of all of the money being spent is inside that one ad out of the 132 ads total.
Look a little more closely and you’ll see the top five already account for 60% of the total spend.
That’s not uncommon. In lots of cases the top three to five ads will account for about half of your ad spend.
Applying the Top N Method
I like to start by doing Top N on spend, because that’s where I can identify a “bleeder” (a high-spend ad with very low return).
Then I look at what drove the most revenue or had the highest number of conversions. Because then I can find where the winners are.
Then I look at clicks, leads, or other metrics that are important to the business.
Using this method, I kill the losing ads and amplify the winning ads.
Let’s say you were to sort just by conversions or revenue. If you do that, then you could have an ad that’s wasting lots of money that doesn’t make it into the top four or five for your most important metrics.
So I use Top N for three or four metrics in succession. Each time it reorders the ad sets or ads or creatives or whatever it is that you’re looking at.
You can use this method to determine ad performance in just three minutes.
Find and Fix the Issue
If something’s out of whack, it could require a big change or it could be something wrong with the tracking.
It could be iOS 14, or the pixel wasn’t on that landing page. It could be the data didn’t come through and it’s delayed. There’s all kinds of things that could play into why numbers aren’t adding up.
A lot of people freak out when sales are way down. Understandable. But many times it’s because of some silly issue. So before you pull the fire alarm, just think, does that really make sense?
I like this particular ad here.
There’s no way we spent this amount of money with no return. So we know there’s an issue. And we know with social media platforms like TikTok, Twitter, and Facebook, their systems often will not show data.
We know that because of the iOS 14 update, impressions and clicks are reported on different frequencies. So you might see a bunch of spend show up before the conversions show up or vice versa.
Make sure it’s statistically significant. Also make sure that you have enough data, so you don’t jump to any conclusions.
We’ve seen these systems spiral out of control. For example, let’s say you decide to reduce the bid amount on a marketing channel when the ROI falls below a certain amount. That seems logical. But if you’re only looking at revenue, not conversions, you might kill off a marketing campaign that was actually working quite well.
Imagine if it all boiled down to a hiccup in the data that caused the downward spiral. Not good. So be careful about that.
Now, if you see that a metric is out of whack and the data looks good, then ask yourself why that campaign isn’t performing as well.
Data and Instinct for the Win
Don’t let everything you do be completely automated and dependent upon rules. A successful marketing strategy requires a human touch.
Don’t set so many rules that the software automatically terminates your ads.
Instead, take a moment to look at how far out of bounds the ad performance is. It could be that you launched a new campaign and you’re doing an AB test or some kind of split test. The winner stays on and continues to win, even when other ads are losing, because you’re trying to find another winner to take its place.
If the cost per acquisition is high, then you can break that down using the metrics decomposition pyramid.
For example, the cost per acquisition will double if:
- the conversion rate is cut in half and the cost per click is the same
- the cost per click doubles and the conversion rate is the same
The cost per acquisition remains the same if either factor doubles while the other one is cut in half.
Always look at your marketing analytics when the cost per conversion goes up. Determine whether it’s because of the cost per click or the conversion rate.
When you run ads using objective-based bidding you don’t have to worry as much about cost per click, click through rate, or conversion rate because the artificial intelligence behind the ad platform is going to seek your target metric.
If the target metric is out of whack, you can decompose it into the underlying metrics.
That’s true for organic traffic. But it’s not as true for paid traffic because the systems are getting smarter and can optimize for the objective you set. Either way you should still look.
This method gets you to look at metrics that matter according to our business goals. It gets you to think about and analyze why the data might be good or bad. And it gets you to outline the actions you’re going to take when goals aren’t being met. Over time you’ll find that the same pairing of metrics change alongside each other. So let’s talk about what these balancing metrics are.
One company we were working with was spending a hundred thousand dollars a month on advertising. When they were unhappy with the return, the analyst on the project adjusted the Google ad campaign. All of a sudden the cost per conversion dropped from $20 per lead to $7 per lead.
But I wanted to know how and why it dropped so dramatically. I found out that this person went into the Google ads campaign and turned off all the campaigns except for the brand search terms. Of course it was going to convert super well!
But the balancing metric was volume. When the analyst “fixed” the cost per conversion, the number of leads dropped from 5,000 leads a month to maybe a thousand leads a month.
The key takeaway here is that if you optimize one metric blindly, you can fool yourself into thinking everything is better when in reality another metric took a nosedive.
Analyzing Like a Scientist, but NOT a Rocket Scientist
Metrics don’t matter, unless there’s a clear analysis that can come from the information. Remember, you’re seeking a diagnosis.
Think like a surgeon or scientist. Start with a hypothesis. If a certain thing happens, what will you do to correct it and what outcome do you expect? If there’s no potential action based on some metric, there’s no need to gather the metrics.
I see companies spend most of their efforts collecting data. No one even knows why they’re using the data. Be strategic and ask, “what are we doing with this data? Is there some meaningful action we’re going to take?”
Maybe there’s another metric that would measure the goal better.
The point of analytics is to figure out whether something is worthwhile. Most of the data you thought was important, doesn’t even matter.
I’ll give you one example. Our client was a large company, but this works for small companies, too.
We were working with an airline, taking one database and matching it against another. They wanted to know things like whether a customer that goes skiing has kids and what their income was.
They wanted predictive models to uncover which customers would be most likely to sign up for their credit card or buy flowers or upgrade or travel to new destinations.
We went all in on the idea that more data is better. After all the time and money spent on sophisticated data models, what we found was that the best predictor of people flying more was past purchase behavior. Not a surprise, right?
In this case, purchase behavior predicted purchase behavior. And the fact that they drove a station wagon, or liked to eat Haagen-Dazs ice cream, might be interesting but it had very little impact on their flying behavior.
Moral of the story, you might find that the most obvious thing is the best place to start optimizing in your business as well. Start thinking about what kind of “if-then” logic you can implement. And don’t dismiss the really simple idea just because it’s simple.
The MAA Framework is Not Just for Advertising
Collecting data allows you to put if-then sequences in place across your business. In Google and Facebook you can set up automated rules using if-then logic. For example, one might be for conversions. If conversions fall below a certain number, then an automated action would be taken or an alert might be sent to whoever’s in charge of that area to let them know there is something that needs their attention.
Here is a table of common if-then scenarios we’ve come across. Start small by looking at just a few of these things.
You’ll find a lot of value when you look at the patterns. For example, look at posts with the highest engagement versus posts with the lowest engagement. What can you learn? What do the high-engagement posts have in common? Is there a cross-over with the low-engagement posts?
Don’t spend all your time messing around inside the tools. Even Google’s head of analytics said that 90% of every dollar you spend on analytics should be on people and 10% should be on the tools.
We see a lot of businesses do the opposite. They spend 90% on tools and 10% on people. The hard truth is, the most sophisticated tools are useless without someone who knows how to make sense of the numbers.
To ensure success, set the framework in place. Make it clear that everyone is accountable for the results.
I hope the metrics, analysis, action framework I’ve just introduced you to encourages you. Data and analytics aren’t really that technical. You don’t have to collect a ton of data, build regression models, or feed your AI any recipes.
Customers buy this over that. It’s not math. It’s not huge databases. It’s not engineering.
The MAA framework is all about understanding the numbers in the context of business performance and goals. Tracking metrics should always begin with the business strategy in mind.
The marketing lifecycle: An overview
Remember when digital marketing was simple? Create content, throw it over the wall, hope for the best.
Note that we said “simple,” not effective.
To be effective is more complicated, and this keeps accelerating. There are so many options, so many channels, and so many audiences, that effective digital marketing requires a term to which people often react strongly—
Very few people inherently like the idea of “process.” It brings forth visions of rigidity and inertia.
But there simply has to be a framework in which to produce and publish effective marketing assets. Without this, you have nothing but chaos from which productive work gets done accidentally, at best.
How did it get this way for the enterprise? How did things become so interconnected?
- Marketing isn’t a point in time, it’s an activity stream. It’s a line of dominoes you need to knock over, roughly in order. Lots of organizations do well at some, but fail on others, and thus break the chain of what could be an effective process.
- Marketing activities overlap. It’d be great if we could do one thing at a time, but the marketing pipeline is never empty. Campaigns target different audiences at the same time, and new campaigns are being prepared as existing campaigns are closing.
- Marketing involves a lot of actors at vastly different levels. There’s your content team, of course, reviewers, external agencies and contractors, designers, developers, and—of course—stakeholders and executives. Each group has different needs for collaboration, input, and reporting.
Some of the best business advice boils down to this: “Always understand the big picture.” You might be asked to do one specific thing in a process, but make sure you understand the context of that specific thing—where does it fit in the larger framework? Where does it get input from? How are its outputs used?
In this article, we’re going to zoom out for an overhead view of how Optimizely One helps you juggle the complete marketing lifecycle, from start to finish, without letting anything drop.
Ideas are born everywhere—maybe with you, maybe with your staff, maybe with someone who has no connection with marketing at all, and maybe from an external source, like an ad agency or PR firm. Leading organizations have found a way to widen the top end of their pipeline—the start of their content marketing funnel—and take in more ideas from more sources.
Good ideas combine. Someone has one half of an idea, and someone else has the other half. The goal of effective collaboration is to get those two pieces together. One plus one can sometimes equal three, and more ideas mean better ideas overall. Creativity is about getting more puzzle pieces on the table so you can figure out which ones fit your strategy.
How do you manage the flow of ideas? How do you make sure good ideas don’t get dropped, but rather become great content? The only way to publish great content is to get ideas into the top end of the pipe.
Optimizely One can streamline and accelerate your content intake using templated intake forms mapped to intelligent routing rules and shared queues. Everyone in your organization can know where content is developed and how to contribute to ideas, content, and campaigns currently in-process. Your content team can easily manage and collaborate on requests, meaning content development can become focused, rather than spread out across the organization.
Campaigns don’t exist in a vacuum. They share the stage with other campaigns—both in terms of audience attention and employee workload. Leading organizations ensure that their campaigns are coordinated, for maximum audience effect and efficiency of workload.
Pick a time scale and plan it from overhead. What campaigns will you execute during this period? In what order? How do they overlap? Then, break each campaign down—what tasks are required to complete and launch? Who owns them? In what stage of completion are they in? What resources are required to complete them?
Good marketing campaigns aren’t run in isolation. They’re a closely aligned part of an evolving body of work, carefully planned and executed.
Optimizely One provides comprehensive editorial calendaring and scheduling. Every marketing activity can have an easily accessible strategic brief and dedicated workspaces in which to collaborate. Your content team and your stakeholders can know, at a glance, what marketing activities are in-process, when they’re scheduled to launch, who is assigned to what, and what’s remaining on the calendar.
Good content takes fingers on keyboards, but that’s not all.
Content creators need frameworks in which to generate effective content. They need the tools to share, collaborate, structure, stage, and approve their work. Good content comes in part from tooling designed to empower content creators.
Your content team needs a home base—the digital equivalent of an artist’s studio. They need a platform which is authoritative for all their marketing assets; a place that everyone on the team knows is going to have the latest schedules, the latest drafts, the official assets, and every task on the road to publication.
Content creation isn’t magic—it doesn’t just appear out of the ether. It comes from intentional teams working in structured frameworks.
Optimizely One gives your editors the tools they need for the content creation process, AI-enabled editing environments for fingers-on-keyboards, all the way through intelligent workflows for collaboration and approvals. Authors can write, designers can upload and organize, project managers can combine and coordinate, stakeholders can review, and external teams can collaborate. All within a framework centered around moving your campaigns forward.
Leading organizations look at content beyond its immediate utility. Everything your content teams do becomes an incremental part of an evolving body of work. Content doesn’t appear and disappear; rather, it continually enlarges and refines a body of work that represents your organization over time.
Good creative teams remix and transform old ideas into new ones. They can locate content assets quickly and easily to evolve them into new campaigns quickly. They don’t reinvent the wheel every time, because they lean on a deep reservoir of prior art and existing creative components.
Digital asset and content management should store content in a structured, atomic format, allowing your organization to store, retrieve, organize, and re-use marketing assets quickly and easily.
Optimizely One gives your content team a place to store their content assets, from text and rich media. Content can be archived and organized, either manually, or by using AI to automatically extract tags. Content can be stored as pure data, free from presentation, which makes it easy to re-use. Your content team will always know where to find work in progress, media to support emerging campaigns, or assets from past campaigns. Brand portals make it easy to share assets with external organizations.
Business happens all over the world in every language. To effectively compete around the world, your content needs to be globalized.
Globalization of content is a holistic practice that affects every part of the content lifecycle. Words need to be translated, of course, but you also need to consider cultural globalization—images and symbols that might change—as well as globalization for numbers, currency, and time zones. Going even deeper, you might have to make design changes to accommodate things like differing word lengths and the flow of text.
Beyond simply changing content, your work process is affected. When does translation happen? Who is authorized to order it? Who can perform it? How do you bring external translation companies into your internal processes, and how does this affect the flow of content through your organization?
Optimizely One helps you manage the entire globalization process, whether it’s done in-house or automatically via one of our translation partners. Your customers can be served content in their language and culture, and you can carefully control the alternate, “fallback” experience for languages not yet available, or when you’re not translating all of your content.
Some experiences need to be visually composed from a palette of content and design components. Designers and marketers want to see exactly what their content looks like before they publish.
In some cases, this is easy—everyone should be able to see what a web page looks like before it goes live. But what about your mobile app? What about display advertising? A social media update?
And what happens when you’re modifying content based on behavior and demographics? If you want to see how your web page will look for someone from California who has visited your site before and already downloaded your whitepaper on their iPhone…can you?
Content no longer leaves your organization on a single channel. Composition and preview is always contextual—there is no single, default experience. Leading organizations want full control over their visual presentation and they know that they need to see their content through the eyes of their customers.
Optimizely One provides the tools to visually compose experiences across multiple channels and can preview that experience when viewed through the personalization lens of whatever demographic and behavioral data you can dream up. And this works regardless of channel: web, email, display advertising—everything can be previewed in real-time.
Content can’t do any good unless it can reach your customers. You need to publish your content to them, wherever they are, which means having the flexibility to push content into multiple channels, in multiple formats.
A consumable piece of media is an “artifact.” Your content is the idea and message that make up that artifact. Leading organizations develop their content separate from any concept of an artifact, then transform it into different formats to fit the channel that will spread their message most effectively.
Sure, make a web page—but also push that content to your mobile app, and into your social networks. Broadcast a text message, and an email. While you’re at it, push the information into the display panel in the elevators. Let’s be bold and broadcast it on the TV screens that play while your customers fill up with gas.
The key is delivery flexibility. The world of content delivery has changed remarkably in just the last few years. It will no-doubt change more in the future. No platform can anticipate what’s coming, so you just need the flexibility to be ready to adapt to what happens.
Optimizely One provides complete delivery flexibility. Our systems store your content separate from presentation, and allow multiple ways to access it, from traditional websites to headless APIs to connect your content to mobile apps or other decoupled experiences. Your content can be combined with internally-stored content or third-party content to provide a seamless “content reservoir” to draw on from all of your channels.
Throughout this lifecycle, we’ve moved from content, to artifacts, and now on to “experiences.”
One person consuming an artifact—reading a web page, listening to a podcast, watching a video—is an experience. Just like one piece of content can generate more than one artifact, one artifact should enable thousands of experiences.
Technology has advanced to the point where all of those experiences can be managed. Instead of every customer getting the same experience, it can be personalized to that specific customer in that specific moment.
You can do this using simple demographic or technographic data—perhaps you cut down the information and make your content more task-oriented when you detect someone is on a mobile device. However, the real power comes when you begin tracking behavior, consolidating information about your customers, and giving them specific content based on what you’ve observed.
Leading organizations have a single location to track customer behavior and data. For every experience, they know exactly what this customer has done, how they’ve interacted with the organization, and they can predict what they’ll do next. Content and artifacts will morph themselves to fit each individual experience.
Optimizely One connects both customer behavior and demographics along with the tools to activate that data to affect your customers’ experiences. Our platform allows you to track customer behavior and match that with customer demographics—this includes behavior tracking for customers you can’t even identify yet. Based on that behavior and stored data, editors can modify experiences in real-time, changing content and design to match to what each individual customer is most likely to respond. Or let the machine do the work, with personalized content and product recommendations.
No matter how much you know, customers will always surprise you. The right answer to persuading your customer to take an action might be something you’re not even thinking of. Or, you might have an idea, but you’re not confident enough to bank on it. And let’s face it—sometimes, you just love two different ideas.
Wouldn’t it be great if you could publish more than one thing?
You absolutely can. And you absolutely should.
Leading organizations let go of the idea that an experience is bound to one version of an artifact. Don’t just write one title for that blog post—write three. Publish them all and show them randomly. Let your customers tell you—by their next action—which one was the right one to use.
Experimentation allows you to try new things without the inertia of re-considering and re-drafting all your content. Ideas can go from your mind to pixels on the screen quickly and easily, and you can see what works and what doesn’t. Try a new title, or next text on a button. Does it give you better results? If so, great, keep it. If not, throw it away and try something else.
Refine, refine, refine. The idea that you publish content in one form and just hope it’s the right one is a set of handcuffs that can be tough to shake. But the results can be impressive.
Optimizely One allows you to quickly create and publish multiple variations of content and content elements to any channel. You can separate your content into elements and try different combinations to see which one drives your customers to move forward in their journey, then automatically route more traffic through winning combinations. You can manage feature rollouts and soft-launches, enabling specific functionality for specific audiences in any channel.
The key to a learning and evolving content team is a transparent and unflinching look into what happens to your content after it’s published.
Analytics need to be considered in the context of the entire content domain. What content performs well but has low traffic? What content is consumed often but never moves customers down their buying journey? Customer behavior needs to be tracked carefully, then used to segment customers into audiences, based on both your content team’s observations and insights provided by AI.
Optimizely One offers complete behavior tracking and content analysis, showing you what content works, what content doesn’t, and what your customers are doing during every step of their relationship with your entire digital estate.
Juggle the entire lifecycle
“Publishing myopia” prevents most organizations from truly benefiting from the power of their content and marketing technology. Too many ideas are undercut by an obsession with the publish button. We rush content out the door and just throw it over the wall and hope it lands.
Within that mode of thinking, great ideas get trapped under the surface. Great content is delivered to only one channel in one language. Great experiences never see the light of day because content exists in only one form. And every customer sees the same thing, no matter how their own experience might benefit from something else.
Remember: the marketing lifecycle is a series of stages
Each stage builds on the last and allows content to grow from a random idea your team takes in from the field and turns it into a spectacular multi-channel experience which rearranges and modifies itself to fit each customer.
Juggling all of the steps in the marketing lifecycle can be done, but it’s easy to lose the forest for the trees and get too myopic about individual steps in this process. Leading organizations step back, consider the entire cycle from start to finish, and make sure their ideas, their products, and their messages are enhanced and strengthened in every step.
Comparing Credibility of Custom Chatbots & Live Chat
Addressing customer issues quickly is not merely a strategy to distinguish your brand; it’s an imperative for survival in today’s fiercely competitive marketplace.
Customer frustration can lead to customer churn. That’s precisely why organizations employ various support methods to ensure clients receive timely and adequate assistance whenever they require it.
Nevertheless, selecting the most suitable support channel isn’t always straightforward. Support teams often grapple with the choice between live chat and chatbots.
The automation landscape has transformed how businesses engage with customers, elevating chatbots as a widely embraced support solution. As more companies embrace technology to enhance their customer service, the debate over the credibility of chatbots versus live chat support has gained prominence.
However, customizable chatbot continue to offer a broader scope for personalization and creating their own chatbots.
In this article, we will delve into the world of customer support, exploring the advantages and disadvantages of both chatbots and live chat and how they can influence customer trust. By the end, you’ll have a comprehensive understanding of which option may be the best fit for your business.
The Rise of Chatbots
Chatbots have become increasingly prevalent in customer support due to their ability to provide instant responses and cost-effective solutions. These automated systems use artificial intelligence (AI) and natural language processing (NLP) to engage with customers in real-time, making them a valuable resource for businesses looking to streamline their customer service operations.
Advantages of Chatbots
One of the most significant advantages of custom chatbots is their round-the-clock availability. They can respond to customer inquiries at any time, ensuring that customers receive support even outside regular business hours.
Custom Chatbots provide consistent responses to frequently asked questions, eliminating the risk of human error or inconsistency in service quality.
Implementing chatbots can reduce operational costs by automating routine inquiries and allowing human agents to focus on more complex issues.
Chatbots can handle multiple customer interactions simultaneously, making them highly scalable as your business grows.
Disadvantages of Chatbots
Chatbots may struggle to understand complex or nuanced inquiries, leading to frustration for customers seeking detailed information or support.
Lack of Empathy
Chatbots lack the emotional intelligence and empathy that human agents can provide, making them less suitable for handling sensitive or emotionally charged issues.
Initial Setup Costs
Developing and implementing chatbot technology can be costly, especially for small businesses.
The Role of Live Chat Support
Live chat support, on the other hand, involves real human agents who engage with customers in real-time through text-based conversations. While it may not offer the same level of automation as custom chatbots, live chat support excels in areas where human interaction and empathy are crucial.
Advantages of Live Chat
Live chat support provides a personal touch that chatbots cannot replicate. Human agents can empathize with customers, building a stronger emotional connection.
For inquiries that require a nuanced understanding or involve complex problem-solving, human agents are better equipped to provide in-depth assistance.
Customers often trust human agents more readily, especially when dealing with sensitive matters or making important decisions.
Human agents can adapt to various customer personalities and communication styles, ensuring a positive experience for diverse customers.
Disadvantages of Live Chat
Live chat support operates within specified business hours, which may not align with all customer needs, potentially leading to frustration.
The speed of response in live chat support can vary depending on agent availability and workload, leading to potential delays in customer assistance.
Maintaining a live chat support team with trained agents can be expensive, especially for smaller businesses strategically.
Building Customer Trust: The Credibility Factor
When it comes to building customer trust, credibility is paramount. Customers want to feel that they are dealing with a reliable and knowledgeable source. Both customziable chatbots and live chat support can contribute to credibility, but their effectiveness varies in different contexts.
Building Trust with Chatbots
Chatbots can build trust in various ways:
Chatbots provide consistent responses, ensuring that customers receive accurate information every time they interact with them.
Chatbots offer instant responses, which can convey a sense of efficiency and attentiveness.
Chatbots can assure customers of their data security through automated privacy policies and compliance statements.
However, custom chatbots may face credibility challenges when dealing with complex issues or highly emotional situations. In such cases, the lack of human empathy and understanding can hinder trust-building efforts.
Building Trust with Live Chat Support
Live chat support, with its human touch, excels at building trust in several ways:
Human agents can show empathy by actively listening to customers’ concerns and providing emotional support.
Live chat agents can tailor solutions to individual customer needs, demonstrating a commitment to solving their problems.
Human agents can adapt to changing customer requirements, ensuring a personalized and satisfying experience.
However, live chat support’s limitations, such as availability and potential response times, can sometimes hinder trust-building efforts, especially when customers require immediate assistance.
Finding the Right Balance
The choice between custom chatbots and live chat support is not always binary. Many businesses find success by integrating both options strategically:
Use chatbots for initial inquiries, providing quick responses, and gathering essential information. This frees up human agents to handle more complex cases.
Escalation to Live Chat
Implement a seamless escalation process from custom chatbots to live chat support when customer inquiries require a higher level of expertise or personal interaction.
Regularly analyze customer interactions and feedback to refine your custom chatbot’s responses and improve the overall support experience.
In the quest to build customer trust, both chatbots and live chat support have their roles to play. Customizable Chatbots offer efficiency, consistency, and round-the-clock availability, while live chat support provides the human touch, empathy, and adaptability. The key is to strike the right balance, leveraging the strengths of each to create a credible and trustworthy customer support experience. By understanding the unique advantages and disadvantages of both options, businesses can make informed decisions to enhance customer trust and satisfaction in the digital era.
The Rise in Retail Media Networks
As LL Cool J might say, “Don’t call it a comeback. It’s been here for years.”
Paid advertising is alive and growing faster in different forms than any other marketing method.
Magna, a media research firm, and GroupM, a media agency, wrapped the year with their ad industry predictions – expect big growth for digital advertising in 2024, especially with the pending US presidential political season.
But the bigger, more unexpected news comes from the rise in retail media networks – a relative newcomer in the industry.
Watch CMI’s chief strategy advisor Robert Rose explain how these trends could affect marketers or keep reading for his thoughts:
GroupM expects digital advertising revenue in 2023 to conclude with a 5.8% or $889 billion increase – excluding political advertising. Magna believes ad revenue will tick up 5.5% this year and jump 7.2% in 2024. GroupM and Zenith say 2024 will see a more modest 4.8% growth.
Robert says that the feeling of an ad slump and other predictions of advertising’s demise in the modern economy don’t seem to be coming to pass, as paid advertising not only survived 2023 but will thrive in 2024.
What’s a retail media network?
On to the bigger news – the rise of retail media networks. Retail media networks, the smallest segment in these agencies’ and research firms’ evaluation, will be one of the fastest-growing and truly important digital advertising formats in 2024.
GroupM suggests the $119 billion expected to be spent in the networks this year and should grow by a whopping 8.3% in the coming year. Magna estimates $124 billion in ad revenue from retail media networks this year.
“Think about this for a moment. Retail media is now almost a quarter of the total spent on search advertising outside of China,” Robert points out.
You’re not alone if you aren’t familiar with retail media networks. A familiar vernacular in the B2C world, especially the consumer-packaged goods industry, retail media networks are an advertising segment you should now pay attention to.
Retail media networks are advertising platforms within the retailer’s network. It’s search advertising on retailers’ online stores. So, for example, if you spend money to advertise against product keywords on Amazon, Walmart, or Instacart, you use a retail media network.
But these ad-buying networks also exist on other digital media properties, from mini-sites to videos to content marketing hubs. They also exist on location through interactive kiosks and in-store screens. New formats are rising every day.
Retail media networks make sense. Retailers take advantage of their knowledge of customers, where and why they shop, and present offers and content relevant to their interests. The retailer uses their content as a media company would, knowing their customers trust them to provide valuable information.
Think about these 2 things in 2024
That brings Robert to two things he wants you to consider for 2024 and beyond. The first is a question: Why should you consider retail media networks for your products or services?
Advertising works because it connects to the idea of a brand. Retail media networks work deep into the buyer’s journey. They use the consumer’s presence in a store (online or brick-and-mortar) to cross-sell merchandise or become the chosen provider.
For example, Robert might advertise his Content Marketing Strategy book on Amazon’s retail network because he knows his customers seek business books. When they search for “content marketing,” his book would appear first.
However, retail media networks also work well because they create a brand halo effect. Robert might buy an ad for his book in The New York Times and The Wall Street Journal because he knows their readers view those media outlets as reputable sources of information. He gains some trust by connecting his book to their media properties.
Smart marketing teams will recognize the power of the halo effect and create brand-level experiences on retail media networks. They will do so not because they seek an immediate customer but because they can connect their brand content experience to a trusted media network like Amazon, Nordstrom, eBay, etc.
The second thing Robert wants you to think about relates to the B2B opportunity. More retail media network opportunities for B2B brands are coming.
You can already buy into content syndication networks such as Netline, Business2Community, and others. But given the astronomical growth, for example, of Amazon’s B2B marketplace ($35 billion in 2023), Robert expects a similar trend of retail media networks to emerge on these types of platforms.
“If I were Adobe, Microsoft, Salesforce, HubSpot, or any brand with big content platforms, I’d look to monetize them by selling paid sponsorship of content (as advertising or sponsored content) on them,” Robert says.
As you think about creative ways to use your paid advertising spend, consider the retail media networks in 2024.
HANDPICKED RELATED CONTENT:
Cover image by Joseph Kalinowski/Content Marketing Institute
8 Best Zapier Alternatives to Automate Your Website
Intro to Amazon Non-endemic Advertising: Benefits & Examples
YouTube Highlights its Top Trends, Topics and Creators of 2023
Watch Live on December 11 – WordPress.com News
Mastering The Laws of Marketing in Madness
Critical WordPress Form Plugin Vulnerability Affects Up To +200,000 Installs
How to Create a Wholesale Order Form in WordPress (3 Ways)
12 Holiday Emails for Customers (Templates & Examples!)
8 Super-Helpful AI Features in Google Ads
With the end of the Hollywood writers and actors strikes, the creator economy is the next frontier for organized labor
WORDPRESS5 days ago
8 Best Zapier Alternatives to Automate Your Website
MARKETING7 days ago
Intro to Amazon Non-endemic Advertising: Benefits & Examples
SOCIAL4 days ago
YouTube Highlights its Top Trends, Topics and Creators of 2023
WORDPRESS6 days ago
Watch Live on December 11 – WordPress.com News
MARKETING6 days ago
Mastering The Laws of Marketing in Madness
SEO6 days ago
Critical WordPress Form Plugin Vulnerability Affects Up To +200,000 Installs
WORDPRESS4 days ago
How to Create a Wholesale Order Form in WordPress (3 Ways)
PPC6 days ago
12 Holiday Emails for Customers (Templates & Examples!)