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Digital Marketing Data and How to Optimize Like a Champ

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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.
  • Diagnose.
  • Treat.

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…

  • Data
  • Campaigns
  • Ads
  • Landing pages
  • Messages

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.

Balancing Metrics

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.

Summary

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. 


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Ascend | DigitalMarketer

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Ascend | DigitalMarketer

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

  1. Speed

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

  1. Automation

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

  1. Access 

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

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

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

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

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

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



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2023 Facebook Algorithm Guide: Overview & Best Practices

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2023 Facebook Algorithm Guide: Overview & Best Practices

Every month, 2.7 billion people use Facebook, Meta’s globe-dominating social network. For marketers, this is an un-ignorable audience. However, reaching that audience isn’t always easy – to get content in front of a relevant user, they need to make the Facebook algorithm work in their favor.

Unfortunately, the algorithm can feel very mysterious. Why do some posts go viral with engagement while others wither and disappear without so much as a few courtesy likes?

The good news is that while the technical rules governing Facebook’s algorithm may be in a black box, there are plenty of guidelines and common-sense tips that can help ensure your content gets prioritized and seen. Facebook has published many explainers and tutorials over the past few years to break down how its algorithm ranks and distributes content to users’ Feeds.

Here’s how Facebook’s algorithm works in 2023 with ten expert tips on increasing the impact, performance and lifecycle of your Facebook content.
 

Table of Contents

 

  • What is the Facebook Algorithm?
  • A Recent History of the Facebook Algorithm 
  • How the Facebook Algorithm Works in 2023
  • 10 Best Practices for Working with Facebook’s Algorithm
  • Final Takeaway

 

What is the Facebook Algorithm?

 
The Facebook algorithm is the set of rules and formulas that determine what content users see in their Feeds. Its goal is to make the posts that “matter most to the user” highly visible to that user. To do this, it analyzes each piece of content eligible to be displayed and ranks them according to a set of criteria.

As Facebook explains, the algorithm is actually “not just one single algorithm; it’s multiple layers of [machine learning] models and rankings that we apply to predict the most relevant and meaningful content for each user.”

If that sounds complex, that’s because of the sheer volume of content on the Facebook platform. There are over 2 billion Facebook users and trillions of posts they can see; the algorithm needs to be sophisticated to sort through all that content in an instant between launching the Facebook application and the population of each user’s Feed. 

 

A Recent History of the Facebook Algorithm

 

Since 2017, Facebook has been increasingly transparent about significant changes in how it ranks and distributes content. That also means the algorithm is constantly evolving. In general, those updates have favored user input, posts friends and family over publishers, and content personalized to a user’s interests… all geared toward generating more “meaningful interactions.”  These updates include:

 

  • Meaningful Interactions Update (2018) – This update signaled that the algorithm would predict which posts a user might want to interact with their friends about and show these posts higher in Feed. These posts inspire discussion in the comments and posts that users might want to share and react to. 
  • Updates to Video Rankings (2019) – This update boosted the rankings of video posts that users sought out and returned to, watched for more than one minute at a time, and were original creations and not repurposed content. 
  • Addressing Sensational Health Claims (2019) – This update applied some of the existing “clickbait” rules specifically to posts making medical or health claims in an effort to reduce misinformation. Exaggerated or sensational claims were deprioritized, as were posts promoting products that advertised “miracle” cures.

 

The past three years have seen additional updates, and since they’re more recent, they deserve closer examination.

 

2020: Key takeaway from 2020

 

In 2020, Facebook modified its algorithm again to give more weight to original, credible news sources and create more personalized advertising encounters for users based on their interactions. Additional updates this year included changes designed to comply with Apple’s iOS 14’s privacy guidelines. 

 

  • Prioritizing Original Sources: In response to users continually reporting a preference for “news stories that are credible and informative,” Facebook announced that it would make ongoing updates that “prioritize articles in News Feed that we identify as original reporting on a developing story or topic.”
  • Personalized Ads: The Facebook algorithm serves advertisements to a user’s Feed based on the posts and pages they have engaged with previously. Businesses are also given the option to share information about the actions that users take on their websites and apps so they can show the most relevant content in users’ Facebook Feeds. To balance this process of information gathering and sharing, which also lays the foundation for personalized advertising on the platform, Facebook instituted the “Why am I seeing this ad” feature and the “Ad Preferences” dashboard for users (and to address privacy concerns).
  • Retargeting Limitations: Even with expanded personalization, Facebook had to respond to the significant privacy and permissioning guidelines i=within the Apple iOS 14 update released in 2020 (Tinuiti’s Liz Emery takes a more detailed look at this topic here). When Apple users install or update to iOS 14, they will be prompted to opt-in or opt out of data sharing. While Facebook has other variables that can be used to identify devices, such as the associated email address and phone number, targeting that depends on users sharing their data at the device level is restricted based on this update.

 

2021: Machine Learning and User Control

 

In 2021, Facebook released new details about how the algorithm governing users’ Feeds works and increased the amount of control users have over what they see. 

 

  • Favorites: A new tool where users can control and prioritize posts in their Feeds from the friends and Pages they choose. By selecting up to 30 friends and Pages to include in Favorites, their posts will appear higher in ranked and can also be viewed as a separate filter.
  • Revealing the algorithm’s machine learning mechanics: In 2021, Facebook published an in-depth post explaining how the Feed predicts what users want to see. For the first time, it detailed the machine learning processes behind predicting what users see in their Feeds based on various factors, including what and whom they’ve followed, liked, or engaged with recently. These mechanics are largely still in place today.

 

Source: Facebook

 

2022: From ML to AI

 

Last year, the Facebook algorithm evolved further in the direction of user control and augmented its use of machine learning tools with more sophisticated artificial intelligence systems. These two updates went hand-in-hand. Users were given a new function on each post they saw, the “Show More/Show Less” feature. Selecting “Show More” would increase the ranking score for that post, increasing the likelihood of a similar post or a similar user appearing in the user’s Feed. The inverse would happen when “Show Less” is selected.

These per-post user inputs are simultaneously helping the AI system generalize how relevant future content will be for that user. Or as Facebook puts it, “by offering more ways to incorporate direct feedback into Feed ranking, we’re making our artificial intelligence systems smarter and more responsive.”

Facebook’s AI model generates what the company calls user and content embeddings, which help predict the types of content a person wants to see more of or less of in their Feed. Another Facebook blog post from 2022 explains that a “user embedding captures a person’s tastes, while the content embedding captures the essence of what a post is about.” 

One last update from 2022 – what was once called the Facebook News Feed is now just the “Feed.” That’s how we refer to it throughout this article, except where relevant due to historical discussion.

 

How the Facebook Algorithm Works in 2023

 
That’s the state of the Facebook algorithm in 2023 – it has evolved to become an AI-powered, user-centric model designed to present users with relevant, welcome content in their Feeds. Even though Meta will admit that the algorithm isn’t perfect (and may never be), Facebook has demonstrated a willingness to modify its processes to give users what they want.

Despite the Facebook algorithm’s complexity and integration of new technologies like AI and machine learning, understanding its core functionality boils down to four ranking factors.

The Four Ranking Factors Fueling the Facebook Feed Algorithm

 
Prioritizing what “matters” to users has been one of the most consistent purposes of the Feed and all of its previous iterations. The goal of Facebook’s algorithm is to “show stories that matter to users,” according to Adam Mosseri, VP of Facebook’s News Feed Management. That aim is reflected across the platform’s many updates and tweaks to its algorithm, from more user control to increased personalization on advertisements. 

With that in mind, you should know how Facebook’s different algorithm factors work together to determine which stories “matter” to a user. And Facebook made these factors easy to understand in its published help center post.  
 

1. Inventory

 
Inventory represents the stock of all content that can display to a user on Facebook’s News Feed, which fluctuates based on user activity once scrolling has begun. This includes everything posted by friends and publishers.
 

2. Signals

 
Signals represent the information that Facebook can gather about a piece of content. Signals are the single factor that you have control over.

These are your inputs that Facebook interprets; type of content, the publisher, its age, purpose, and more.

You want your content to signal to Facebook that it’s meaningful and relevant to your target audience.
 

3. Predictions

 
Predictions represent a user’s behavior and how likely they are to engage with a content piece. Will a user watch a video to completion? Will they select the “Show More” feature on the post?

Predictions take authentic engagement like comments, likes, and shares from real profiles into account.
 

4. Relevancy Score

 
Relevancy Score is the final number assigned to a piece of content based on the likelihood that the user will respond positively to it. It also accounts for whether a post is “clickbait,” whether it links to a low-quality webpage, or if it’s misinformative in some way.
 

10 Best Practices for Working with Facebook’s Algorithm

 
So how can you tailor your content to ensure a high Relevancy Score and a strong enough ranking to appear in your target audience’s Feeds? Most of the following tips will be common sense if you currently produce content for social audiences, but many are specific to the sophisticated Facebook algorithm. 

Here are some guidelines and best practices for keeping your content meaningful in Facebook’s eyes, based on our research, Facebook’s recommendations, and Matt Navara and Paul Armstrong’s coverage of Facebook’s News Feed webinar
 

1. Keep posts relevant to your audience

 
Your content should always be relevant to your core audience — the people you want to build a community around. If your content is relevant to a user, the Facebook algorithm is likely to interpret that content as “meaningful,” a key consideration in ranking. 

Stories should be compelling enough for a user to want to share with family and friends. Content should be informative and interesting… and, of course, accurate. 

Products, education and lifestyle imagery, should reinforce your post’s meaningful and informative nature and build on your identity as a brand answering to a specific audience.

 

2. Engage readers and encourage interaction

 
Facebook’s News Feed algorithm favors content that fosters positive interactions between your followers and others.

Any piece of content, from products to education to entertainment — should provoke conversation. Remember that conversations can’t be one-sided; you want your audience to respond, but you must also respond to them when possible. 

You want your content to prompt people to stop their scroll, interact, and share. Interaction is a crucial weighting factor for the Facebook algorithm, so all your content should be tailored to maximize engagement.
 

3. But don’t use clickbait or engagement bait

 
 
Remember all those “like if…” and “share if you are…” posts?

This is considered engagement baiting; it doesn’t add value or interaction for users. It may not entirely be clickbait, but the Facebook algorithm will penalize it as though it were. 

Avoid asking people to “please comment, like, and share.” Your content should inspire them to engage without having to ask.

Facebook penalizes brands that encourage comments, likes, and shares on organic and ad posts. Keep this in mind when developing content for Instagram and Facebook.

 

4. Expand your post reach with employees and brand advocates

 

Because the Facebook algorithm gives preference to posts from users’ friends, families and the pages they interact with, your company’s Facebook page will have naturally limited reach. This is where enlisting employees and brand advocates can have a real impact. 

Facebook represents your widest audience, but to reach them, you need to engage the audience closest to home. Encouraging your work team to share your brand’s content with their networks broadens the reach of the post or piece of content and your brand. Directly engaging with Facebook users who are already devotees of your brand and asking them to share content with their friends and family can have a similar effect.,
 

5. Or put ad dollars behind content with organic momentum

 
 
The new Facebook algorithm values content that performs well organically, and you can build off that momentum by boosting or promoting that content with ad dollars.

Content that already has strong organic traction means lower CPCs which, combined with ad dollars, can act as a snowball effect for your content.

Identify opportunities for ads based on organic post engagement and tap into Facebook Ads Manager tools by leveraging these posts in ads.

Conversely, don’t waste ad dollars on poor-performing organic content. It will have higher CPCs and cost you more while offering less in return.

“If a post performs well with engagement, likes, and shares, there’s an opportunity to place additional ad dollars to drive that performance even further.”

— Nii Ahene, Chief Strategy Officer at Tinuiti
 
Portrait of Nii Ahene
 

6. Create compelling, original video content

 
 
2019 was the year that Facebook began leaning into its video offering in earnest, and it hasn’t stopped since. Today, the video formats available on Facebook have expanded to include Reels and Stories (shorter clips), Video on Demand and Live video. Reels, in particular, is Facebook’s fastest-growing content format “by far.” s video continues to be the top-performing content type across all social media networks, focusing on video should be a central part of your Facebook marketing strategy.

For your video content to perform best in the Feed, Facebook recommends that it be original, capture the audience’s attention, spark engagement, and inspire users to seek additional video content from the same source. 

To create original and authentic Reels, Stories and full-length videos, make sure they capture your brand’s voice and avoid duplicating content. To retain attention, ensure your creative and copy is optimized towards mobile viewing (i.e., shortened copy, readable overlays, shortened headlines). And to generate engagement, encourage discussion and genuine interactions (but like always, avoid engagement bait).

 

7. Inspire audiences and evoke emotion with storytelling

 

Just as videos should be original, engaging and attention-grabbing, so should any content you post on Facebook. Understand the kinds of stories that resonate with your audience and craft your posts to tell those stories in an exciting way.

You can create connections with your audience through authenticity, interactivity and accuracy. But the surest way is by listening. Ask for feedback. Learn their interests. Take cues from their activity on other platforms. When you know what your audience cares about, you have a better chance of inspiring them… and a better chance of rising to the top of their Feeds.

 

8. Post authentic and truthful content

 

Facebook says that “authentic stories are the ones that resonate most” and that users want to see accurate information. After the controversies surrounding “fake news” and the spread of dis- and misinformation on the platform in recent years, the company has made promoting truthful content central to the Facebook algorithm’s function. 

To signal that your content is genuine and accurate, write clear headlines free from exaggeration or sensationalism. Use well-sourced, reliable information, and avoid sharing content from sources you need clarification on. And above all, don’t lie or try to mislead with your content.

 

9. Schedule content when readers are likely to engage

 

The Facebook Feed is no longer chronological, but timing can still impact post performance within the algorithm. You want to post content when your audience is likely to engage with it, which is likely in the evening or overnight, but it can vary widely by the user. There is some research exploring the objectively ideal time for posting, but the ultimate best practice is understanding your audience and when they are most likely to be on the platform. 

 

10. Learn what works by tracking content performance

 

After you’ve published your content, remember to use Facebook Insights to track the performance of your content. This will help you understand how your different content pieces are performing in terms of engagement, which is the key ranking metric. 

Facebook also offers a variety of tools designed to help you measure both organic content and paid ads. Choose the best tools for your brand, and track performance regularly. Learn from your own Insights data and the tools you use, and optimize your content from there.

Final Takeaway

 
The Facebook algorithm is sophisticated and constantly evolving. There are few shortcuts and no way to “hack” it. But the steps outlined in this article can help make the algorithm work for you and help you get your content in front of the Facebook users who need to see it.

Want to work with our team of Facebook experts? Reach out today!

Editor’s Note: This post was originally published by Greg Swan in April 2020 and has been updated for freshness, accuracy, and comprehensiveness.

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Five questions for our new CMO, Shafqat Islam

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Five questions for our new CMO, Shafqat Islam



Alex Atzberger: Now that you’ve stepped into the CMO role, what are you looking forward to?   

Shafqat Islam: It’s amazing to take on this role at both a category creator and leader. How many brands can be a leader in almost every category–think Experimentation and CMS–that we play in?  

And we have so much to look forward to and build on. We have an exceptional team of marketing leaders and practitioners. They are fiercely intelligent, optimistic, and care deeply about what our products can *do* for our customers. Not just for the people who will encounter the marketing, retail, and product experiences that we support, but for the people who build them. As somebody who has both built products and been deeply immersed in marketing, I love the perspective that our team has.  

Alex Atzberger: What makes Optimizely unique?   

Shafqat Islam: First off, we’re category creators in experimentation and content management, both CMS and CMP. Marketers know this, and analysts know it, as something like 7 major analyst reports will tell you.  

Martech is a crowded field, so it’s true that there are a lot of firms whose territory overlaps with some of ours. But show me another company that can handle the entire content lifecycle like we can. Or show me another company that can do both feature flagging and experimentation.  

We also have a legendary legacy in the martech world. Before I joined, I knew that A/B testing and Optimizely were synonymous, and that the company’s roots go all the way back to the origins of the practice. And that’s something that is like common folklore in marketing and technology.  

And more than anything, the 1500 people who work here are world-class. 

Alex Atzberger: Being a CMO talking to other CMOs and marketing leaders is an advantage. You know the customer. But you’ve also built tech products. How does that affect your work now?  

Shafqat Islam: I’ve spent the majority of my adult life building products for marketers. So I’ve been lucky to spend so much time talking to CMOs and marketers in almost every type of company all over the world. As the founder/CEO of Welcome, my approach was to solve marketer challenges by building products. But now as CMO, I get to use the products we build.  

We’re practitioners of all of our own solutions, so in addition to the natural empathy I have for marketers, I am also close to the job’s unique challenges every day. There’s nothing like that to keep you sharp and keep you close to the customer.  

As a product builder, I knew we must always speak to business outcomes. But as CMO, I love that we aren’t just talking about the solutions – we’re living them, too.  

Because I was an entrepreneur for so long, I also bring another unique view – my willingness to take smart risks. I love to try things, even if (especially if?) the results are sometimes surprising. When it comes to experimentation, there are no failures, only learnings. 

Alex Atzberger: What are the biggest challenges you’re hearing from our customers, current and future?  

Shafqat Islam: Growth, especially given how tough it is out there for so many industries. The stakes are very high when it comes to creating experiences that will win and retain customers. That’s what all of our customers–especially the retail heavyweights-are thinking about.  

And marketing and technology leaders need to do this with leaner budgets. Efficiency matters a lot right now, and that means not only reducing the costs you can see, like the price tag attached to software, but also the costs you can’t see right away, like how much time and money it takes to manage a set of solutions. With that said, in tough times, I think the strongest brands can not just survive but also thrive. I also think when others are fearful, that may be the time to invest aggressively. 

And in the background of all this, there is still the ever-expanding list of customer touchpoints. This is simultaneously an exciting challenge for marketers and an exciting opportunity. More data means more effective storytelling– if you can use it right.

I also hear marketers when they say there’s a need for a shared space for collaboration among us. The role of the marketer is expansive, and it’s only getting more complicated. Building a community where we can come together and appreciate our shared goals is difficult, but I’m optimistic that we’re moving in the right direction.  

Alex Atzberger: What is next in our space? What will marketing and technology leaders be talking about six months from now?  

Shafqat Islam: Looking around now, it’s clear that 2023 will be the year that AI-generated content goes mainstream. We’re just starting to see the uses and the consequences of this. There’s already buzz about ChatGPT and its capabilities, and platforms are already making space to integrate AI functionality into their offerings. It could be an exciting way for users to become better equipped to create and share high-quality content.  

Customers also have gotten very used to personalization. Every screen they see daily is personalized, whether it’s their Netflix account or social feeds. So, when I see a site that isn’t personalized, I kind of scratch my head and wonder, why? With personalization now the norm, expectations for digital creators are sky-high.

Read the official press release.


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