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By now, you’ve probably read Part I of this series: How to Identify Root Cause. You went through the steps, identified poorly performing accounts, campaigns, ad groups, keywords, and product groups. But while it was a great exercise, in the end, you likely came to the conclusion that performance was dropping everywhere -- and that includes numerous dimensions.
So you might be wishing you could get the two hours back you just wasted following our suggestions. However if performance is dropping everywhere, as opposed to just one segment of your program, it likely means there is a dimension that is performing worse than others -- and it’s up to you to identify what it is.
What is a Dimension?
At this point, you're probably wondering what do you mean by “dimensions?” Whenever you click on an ad, the click will either come from one of three devices -- a computer, phone, or tablet. This click will always come from a specific location and happen at a specific time of the day. These categories of device, location, and time of day are subsets of all possible dimensions from where clicks can originate.
How Do Dimensions Relate to Performance?
Certain categories within dimensions have more weight than others. When looking at device-level spend, you might see that 90% is attributed to ad clicks from computers. As a result, if performance from computers starts to drop, we would see performance of the whole account dropping in aggregate.
This example might illustrate the relationship between dimensions and performance more clearly: a 26-year-old male living in Los Angeles is searching for a “red shirt” on a Sunday at 5pm on his computer. He is desperate to find one, so he clicks on the first retail ad that pops up, and purchases a red shirt to be delivered to his apartment.
He has a 23-year-old female friend, who lives in New York, and is also searching for “red shirt” on a Tuesday morning at 11 a.m. on her phone. She clicks the same retail ad he did, but chooses not to purchase a red shirt because she didn’t like it.
The keyword from these two clicks are the same, but the following dimensions differ:
Maybe it's possible conversion rates for red shirts are higher on desktop than mobile. Or it’s possible there is a larger variety of red shirts for males than females. It's also possible the inventory of red shirts for this retail store varies by location, time of day and day of week.
The point is, there are LOTS of dimensions attributable to clicks, and it’s likely these dimensions exhibit variance in behavior. Because of this, you need to adjust bids based on dimensions in relation to how they tie into performance.
Now you have to do the dirty work of figuring which dimension is causing a drop in performance. With so many dimensions to choose from, you can potentially waste hours going down the rabbit hole. Prior to diving into exploration, asking the following can help you identify the poorly-performing dimension more quickly: Have any changes occurred recently that could have affected performance for a certain dimension?
Going back to the above “red t-shirt” example, there might have been a drop in available male t-shirts month-over-month due to dwindling inventory that caused Return on Ad Spend (ROAS) to decrease, yet males were still clicking on ads (but couldn’t convert because there was no inventory to buy).
Once you have a hunch about which dimension might be dropping performance, don’t hesitate to explore the data. Set a pre-post period and visualize the data to get a pulse on what is actually going on.
Example: Device Performance
Let’s say from September to October 2018, your ROAS dropped from 200% to 150%:
You strongly suspect the drop is coming from a specific device. The next step would be to split this chart by device to assess this theory:
At this point, it's very clear that the drop in performance is coming strictly from mobile devices. From here, you will have to dig one step deeper to figure out WHY performance is dropping in mobile. Maybe you changed your mobile landing page in October. Perhaps load time suddenly started slowing down due to architectural changes within the landing page. There are lots of possibilities, but if you dig deep enough, you’ll likely find a reason.
Dashboards, Dashboards, Dashboards
With so many dimensions, it’s hard to keep track of when a dimension is performing well or poorly. Yet, this knowledge can save you hours of time troubleshooting. This is where dashboards come in - they take a lot of work upfront to satisfactorily establish, yet will save you a lot of troubleshooting time in the long run.
With so many types of dashboard software available, it might be difficult to settle on one that satisfies your needs 100 %. However, at the end of the day, you can’t go wrong with most options. Examples of useful dashboard software include:
Internal Alerts
As useful as dashboards can be, it can be easy to forget to take action on the insights and information they provide. Setting up logic that returns alerts is also a solution that can help you flag poor performance,(e.g. if last week’s ROAS was 10% worse than the ROAS before that, send an alert) These alerts can either be set up locally on your computer or programmed into internal communication software such as Slack.
Although there might be false-positive alerts, if set up correctly, they should provide a net gain in troubleshooting time savings.
Once you determine which dimensions are failing, you need to make adjustments. In the device example above, you saw that mobile was performing worse than other devices. Because mobile was losing efficiency, you shouldn’t drive as much traffic toward mobile. So the next logical step here would be to drive traffic away, which you can do by lowering the bid adjustment for mobile.
For example, there might be an existing mobile bid adjustment of 50% for mobile in all your ad groups. You would want to drop this number down. How much you’d want to drop it completely depends on how much data is attached to mobile; if you're not sure how much to drop it by, drop it in 5% increments, and monitor closely day over day to see how these drops are affecting spend.
The granularity at which you can set bid adjustments varies by dimension. The following table illustrates the most granular you can set your dimensional bid adjustments at:
Any of these ad group dimensions can be set at the campaign level. But it’s very unlikely all ad groups will follow the same performance trends by dimension -- which is why you always want to make sure you are setting bid adjustments at the most granular level possible.
Understanding performance by dimensions is important for understanding how your PPC program operates, but more importantly, it’s essential for troubleshooting what might be causing a drop in performance. As we’ve seen in this series, a drop in performance can be caused by a number of different factors; being able to determine whether or not a specific dimension is contributing to this drop will help you determine the best next steps for action, paving the way for you to meet -- and exceed -- your PPC goals.
By now, you have become an expert at identifying the root of problems and what dimensions are failing. However, it still might not be enough to solve the overarching problem of how to bring performance back to expected levels because you might not be optimizing toward the most efficient metric in the first place. In Part III of our series, we cover how to address situations in which you might need to reassess how you are optimizing your program.
As a digital advertiser, you know that PPC advertising is a valuable tool to drive all sorts of marketing goals, such as finding new leads, nurturing prospects, driving conversions, and increasing the lifetime value of your current customers. But in order to be effective and profitable, PPC requires ongoing financial investment, constant analysis and continual adjustments to ensure maximum ROI. As part of that recipe, it’s critical to know how to calculate Cost Per Click -- or your maximum CPC -- and to get it right.
The good news for digital advertisers is that CPC is the one factor over which you have the most control. And CPC has the most significant impact on performance. Maximum cost per click affects:
So it’s a constant balancing act. Set CPC too low and your ads might not even appear or be seen. Set CPC too high and you can end up grossly overspending for ad space.
When you perform keyword research using Google Ads Keyword Planner, it provides an average CPC bidding range that's needed to appear at the top or bottom of the page for certain keywords. PPC advertisers can use it as a guide to what they might spend to reach a certain ad position. But to ensure you have efficient PPC campaigns that maximize ROI, it’s essential to calculate maximum Cost Per Click for yourself.
The reason? You run a unique online business and you need specific profit margins to justify your PPC advertising spend and keep your business growing. Relying on Google’s averages to guess the right CPC leads to mediocre results at best, and negative ROI at worst. You need to evaluate your own market and optimize your PPC strategy to truly meet and exceed your business goals. Read on to learn how to calculate maximum CPC for Google Ads.
In order to accurately calculate Cost Per Click, the first thing you need to know is the value of your customers. How much money do your customers spend with your business on average?
When calculating your CLV (customer lifetime value), don’t forget to first determine the real profit you get from your product. So you need to take into consideration taxes, shipping costs, and the overhead expenses for administrative tasks. Your product can have a list price of $99, but your actual profit is more like $50 after you factor in these internal costs. You also need to consider internal costs when calculating your CLV, or you will end up grossly overspending on ad space.
Depending on what kind of product or service you offer, this can be based off of a single purchase or average of purchases over time. For example:
Because every business has a unique setup and expenses, determining your internal costs is probably the most difficult part of calculating your CLV. But it’s important to include a calculated estimate here, or risk seriously overestimating your CLV. You will use your CLV to help make sure you don’t spend more on advertising than you earn from it.
The next thing you’ll want to figure out is the average conversion rate on your website. Specifically, of the people who visit your website, what percent convert into paying customers? This will help you determine how many clicks are required for a conversion.
For example, if you get 50 sales for every 1000 website visitors your conversion rate is 50/1000 = 5%.
Your conversion rate is a static number. That said, it can change over time. And you can create and optimize targeted landing pages designed to boost your conversion rate, which impacts your CPC.
The best way to calculate your conversion rate is with your existing analytics software. You can use Google Analytics Goal Tracking or eCommerce tracking to see your conversion rate based on current data.
If you already have PPC campaigns up and running, check your conversion rates for specific ads, landing pages, and keywords. The only problem with this strategy is targeting branded keywords: people who type your business name into search are already familiar with your brand and more likely to convert as a result. Including conversions from branded queries in your calculation can artificially inflate your average conversion rate. Avoid including branded keywords or find another method to calculate a more balanced conversion rate.
At this point, you have all the information you need to calculate a CPC that makes you zero profit but incurs zero losses. To be clear, this is not your final CPC. It is a base number you use to decide on the right CPC for your business needs.
Let’s say you calculated your customer lifetime value at $50, and your conversion rate at 1%. Multiplying these numbers together gives you your base CPC: 0.01 x $50 = $0.50
That means you can spend 50 cents per click and spend (on average) the same amount that you earn from sales. Your ROI would be $0.
Of course, this number should not be your maximum CPC. After all, you need to profit! To do this, you’ll want to set your maximum CPC lower than this number, but it needs to be balanced. Set your maximum CPC too low and it limits your ability to drive clicks and conversions from PPC. Because you’re competing for ad space, bidders with a higher CPC will get higher ad positions in search results, which receive significantly more clicks than ads at the bottom of the page. Set your max CPC even lower, and your ads won’t appear in search results at all.
The question for you to answer is how close to your base CPC you should bid to maximize visibility, clicks, conversions and profit. It’s important to remember that your max CPC will never equal your actual CPC. You’re set up to only bid the amount needed to win the auction. So your actual CPC can be lower than your max CPC.
For example, if you set your max CPC as $0.45, your actual CPC could end up being $0.36. With that in mind, you can set your max CPC much closer to your base CPC and still deliver positive results.
The best way to test your market and the bidding landscape is by trying and testing different max CPCs below your base CPC threshold. For example:
Start with one of the percentages in the middle and monitor performance. Then adjust to a higher or lower percentage and see what impact it has (if any) on ad visibility, clicks, and conversions.
If you want to ensure you that maximize ROI from your PPC campaigns, you should regularly recalculate and optimize your CPC. Google uses a variety of factors to determine actual CPC -- improve these areas and you can potentially reduce the costs needed to reach your advertising goals.
Some areas to optimize and improve include:
Google Ads prioritizes relevance and quality over bid amount, determining these factors by using a metric called Quality Score. The higher your quality score, the less you need to bid to rank for a specific keyword. So pay attention to your quality score and the factors that affect it, such as your landing page and ads.
As mentioned before, you can create targeted landing pages designed to maximize on-site conversions. Your conversion rate is a huge factor in determining CPC. Improving your landing page conversion rate from 0.5% to 1% can mean moving your base CPC from $0.42 to $0.85. So create different versions of your landing pages using different headlines, copy, supporting media and calls-to-action, and test and discover which elements are the most effective at driving conversions from your PPC traffic.
Creating more compelling ads can improve your click-through rate and provide more conversion opportunities. This indicates relevance and can improve your quality score. Because you need to ensure your advertising message is sufficiently relevant to the related keyword, using ad extensions and other strategies to make your ad more prominent can also drive more clicks.
Of course, the current state of the market and the bidding landscape can also have a big impact on the max CPC needed. It’s worthwhile and recommended to regularly calculate and adjust your CPC manually. But there’s no way to effectively keep up with the quickly changing markets without relying on automation.
Bid management tools offer a proven strategy to make necessary adjustments to your CPC while reducing wasted ad spend and maximizing ROI. Using data from Google Ads performance and the latest market insights, bid management tools take on the challenging task of ensuring you always set the right CPC. At the end of the day, knowing that you’re on a path to higher ROI frees you up to focus on growing your business, increasing revenue and taking your PPC strategy to new levels.
As a digital marketer, you know by now that not everything goes according to plan the first time around. Sometimes it takes trial and error. Changing it up. Taking a slightly different route. And just doing things differently until you get it right -- or get what you want. That’s the concept behind remarketing. Essentially remarketing is the art of serving targeted ads to people who have already visited or taken action on your website -- an investment that has the potential to significantly increase your advertising costs before driving ROI -- so you have to be judicious about how it’s executed. But, if implemented correctly, it also has the potential to be an extremely valuable advertising strategy. Consider these statistics:
Let’s face it, these days, the success of your PPC program -- and your SEM performance and strategy as a whole -- is contingent upon data. Accurate, reliable and applicable data. And nowhere is this more important than in your bidding strategy. In fact, your competitive success and relevancy in the market depend on it.
As you probably know by now, data is the fuel to your SEM engine, enabling you to devise comprehensive PPC strategies, create progressive business goals and drive future marketing decisions. In short, data is critical in driving your business forward toward peak SEM performance. Thus, the best and most efficient strategies will thoughtfully take into account increasingly more -- and higher quality -- data from key sources.
But what if your SEM performance isn’t up to par? Or you’re not meeting critical business goals? Or competitors always seem to be a half-step ahead of you, beating you to the proverbial punch? The other side to this double-edged sword, of course, is that if your SEM performance is suffering, it’s likely sourced to a data problem as well. More specifically, chances are your current PPC solutions are utilizing incomplete or low-fidelity data to power your bidding strategy, which ultimately fails to give you the necessary big-picture of both your customer and competitive landscape. Thus, any bidding strategy you attempt to employ is almost sure to miss the mark or otherwise fall short of expectations.
There are few things more frustrating. By now, you’re likely tearing out your hair, wondering how in the world you’re going to generate required leads, or meet conversion metrics, let alone exceed them this quarter. We feel your pain. That’s why we’re here to help with a new series that takes a hard and thorough look at the numerous pains common to at-scale SEM/PPC programs.
In the first of our Enterprise Paid Search Pains series, we examine some of the reasons Paid Search programs continually suffer from poor data utilization and sub-standard SEM performance. From there, we dive into real-world data issues you have likely encountered with technology solutions in your day-to-day campaign efforts -- everything from solutions that can’t integrate a full set of historical data or have trouble integrating data from third-party sources to solutions that take too long to incorporate bid data.
And of course we provide you some relevant tips for resolving some of your biggest data issues, while directing you to technologies that truly address any one of these data challenges you might be experiencing. We’ll even let you in on a little secret -- finding just the right tool will help you to collect more data, align it to publisher activity, and automate bidding optimization in a way that is sure to result in the best possible performance for your business.
After all, here at QuanticMind, we want to see you reach peak SEM performance in all areas of your SEM program, whether that’s knocking your quarterly PPC metrics out of the park, reaching new customers or achieving higher ROI than ever before.
And we take pride in not only helping others reach peak performance, but taking their PPC programs to new levels. To your success!
[Learn what pains marketers are feeling and overcoming in paid search HERE.]
Marketers know they need to be active on social media, but what exactly does that mean? Sure, it's important to engage with your audiences and comment when discussions arise, but there are customer conversion opportunities you may be missing if you're not utilizing the power of social media ads. You can't just slap an ad on the Internet and call it ‘good.’ There are best (and worst) practices that can bolster sales or ruin reputation.
The best Facebook ad examples incorporate relevant messaging, visual stimulation, and enticing value propositions.
Here are effective social media ad writing practices:
Use Your Brand Voice
You've likely designed a particular persona for your brand. Be authentic when talking to potential customers. If your brand is edgy and quirky, the voice used in your ads needs to speak in the same tone. If your brand voice is authoritative and fact-based, that needs to come across in the advertisements you display to the public. Utilizing a narrative that's true to your brand will attract the customers you want.
Simplify Ad Copy
Keep it short. Really short. Social feeds are cluttered with ads and distractions. Provide simple ad copy that hold audiences’ attention in as few words as possible. Use photos or videos to captivate people so they're engaged with the message you're trying to send them.
Remove Anything That Doesn't Have Immediate Value
Get rid of fluff, extra words, and anything that doesn't instantly communicate value and the benefits your brand offers people.
Make Benefits Immediately Apparent
Why should anyone buy your product or visit your site anyway? Your audience needs to understand the benefits you're bringing to the table from the beginning.
Start With a Question
What works for social ads? Questions are a great way to pique the interest of people who may otherwise just scroll by your ad. Start with a question relevant to what your target market needs or wants. Then, immediately answer the question with a solution you're able to provide.
Use ‘Revealing’ Words
It's all about creating buzz and making people feel like they're getting insider information nobody else has. Use evocative words that step outside the box and get readers' attention.
Speak Directly to the Reader
You're talking directly to your audience, so they should feel connected to the words you're saying. Use "you" to address your audience as much as possible. Your ad is really a conversation between two people.
Use Brackets
People are more likely to click on a title when it includes brackets. For example, your title might be, “The Power of Increasing Social Media Ad Sales [Webinar].” In this instance, your audience already knows the benefits you're going to provide, and the bracketed information gives them greater insight, thus enhancing overall interest.
Use Strategic (Not Spammy) Capitalization
There's a fine line between proper grammar and going overboard when it comes to online ad space. Make sure you're using proper capitalization, and add strategic caps when warranted, but be sure to avoid ultra-spammy capitalization. That can immediately be a turn off to readers.
Utilize Ellipses
Ellipses (the three dots that typically add suspense to a statement) can really draw readers' attention to your ad. What are you going to write next? This arouses intrigue without using important ad space.
Experiment with Ad Lengths
Everything digital is an experiment. It's a continually evolving process, which means you will constantly adjust your approach to help ensure you hit the right position. The definition of "appropriate lengths" varies from platform to platform. On Twitter, you have up to 280 characters, but the recommended length is closer to 120. Some of the most successful ads on Instagram only feature two or three words. On Facebook, the recommended text space is 125 characters.
Test Calls to Action
Steer clear of using the same call to action on every post. Get creative with your approach. "Learn more" tends to be consistently effective on Facebook. Look for ways to touch your audience and incite them to take action. Instead of "Contact us" try "Reach out to us." Replace "Call us" with "Send us a line." Mix it up.
Test Display URLs
URLs should be short, clear, and concise. Test different display URLs until you achieved optimal visibility. Effective URLs are not only great for customers who have already found you; they'll enhance your online visibility by making your site more SEO-friendly. This is a win-win that'll also get you "in" with the search engines.
Keep these tips in mind as you launch your next social ad campaign.
Speech recognition. Virtual assistants. Self-driving cars. If you’re a Sci-Fi fan, or if you’ve ever seen a classic apocalyptic movie, you likely know that the concept of intelligent machines is hardly new. Historically it’s been the fodder for books, movies and imagination for the past few generations. But the last several years have shown us that Artificial Intelligence is not only here to stay, but is not-so-gradually disrupting industries and changing our lives.
That said, contrary to popular perception, AI likely won’t supplant digital marketing jobs anytime soon -- but rather help strengthen digital marketing strategies and make the jobs of digital advertisers and marketers more productive, efficient and easier in general. In the following, we’ll provide a brief history of AI, explore the different types and use cases of the technology, and discuss how this technology is becoming a critical and necessary tool in an increasingly sophisticated digital marketing arsenal.
So what exactly is Artificial Intelligence? At its core, Artificial Intelligence (AI) is an advanced software-based technology that combines sophisticated computer programming with elements of human intelligence in various combinations to complete a wide range of functions previously thought only possible by humans.
The concept of AI has its origins in the the development of stored-program electronic computers. Computer scientist John McCarthy first coined the term “Artificial Intelligence” at a Dartmouth College conference in 1956. But while the study of AI started to gain momentum, interest waned in the 1970s and eventually the government withdrew funding for the technology's development. Although bringing AI to real-world scenarios was never quite realized over the next few decades, the concept of AI, or intelligent machines, surfaced erratically in popular movies such as Blade Runner, Terminator, and War Games. Then IBM’s computer touting early-stage AI capabilities beat a Russian Grandmaster chess champion in 1997, turning the heads of the scientific community along with the rest of the world, and rejuvenating interest in potential real-world applications of the technology.
Flash forward a few decades, and Artificial Intelligence is becoming less of a luxury and more of a necessity for numerous industries around the world. A 2017 IDC Future Scapes report noted that 75% of developer teams planned to actively implement some type of AI in at least one service or application in the next three years. What’s more, global analyst firm Gartner predicts that by 2020, 85% of customer interactions will be managed with no human involved. The implication of course, is that AI is well on its path to upending and revolutionizing numerous industries -- including digital marketing.
At a high level, there are three types of AI systems: the first one is designed and programmed to perform specific tasks or adhere to certain requests. The second is designed to greatly outpace human cognitive performance. And the last one combines AI technology with elements of the human brain.
Intelligence from Data Algorithms
If you’ve ever told Siri to find the nearest taqueria or told Google to play your favorite indie rock tunes, you know that these systems can understand and process a human command, and then respond intelligently -- at least most of the time.
Perhaps the most common, recognizable, and ubiquitous form of Artificial Intelligence can be found in virtual assistants such as Apple’s Siri or Amazon’s Alexa, which leverage copious data inputs to emulate certain human behaviors with the aim of achieving very specific tasks. The learning process includes natural language processing (NLP) capabilities that enable these systems to understand and communicate human language. This capability in turn enables these systems to acquire information, along with a limited ability to reason and self-correct when they’ve made errors.
Artificial Super Intelligence
Think Artificial Intelligence but on steroids. As its name implies Artificial Super Intelligence is a technology with capabilities that greatly surpass normal human intelligence and cognitive thought. In short, it can easily exceed almost all human activity. In addition to being able to solve complex problems, this advanced technology also outpaces humans in numerous other areas as well, such as creativity, social interaction, and wisdom.
While still being developed, these highly sophisticated intelligence capabilities are achieved through digital emulation of a human brain by replicating the brain’s neural network and linking to a computer interface, putting us one step closer to true man-made human intuition that thus far, has been the stuff of futuristic movies.
Artificial Intelligence and the Human Brain
The blurred lines between humans and machines might be closer than we think. One tech start-up, backed by Tesla’s Elon Musk, is attempting to actually blend human brain activity with the enormous computing power of AI-driven intelligence in an effort to enable people to keep up with AI-enabled devices in terms of problem-solving and other processing capabilities.
So far, we’ve discussed Artificial Intelligence based on data algorithms, Artificial Intelligence that's more intelligent than people and Artificial Intelligence technologies that integrate with human brains. So how does that impact digital advertising?
Well, in a lot of ways. In fact, Artificial Intelligence is becoming an increasingly essential tool in the digital marketers’ toolkit, with more advanced capabilities that help marketers identify and refine their targets, improve marketing strategy and give a big boost to ROI.
Personalized Email Campaigns
Of its numerous benefits to marketers, Artificial Intelligence is critical for helping scale email marketing efforts, particularly when it comes to analyzing audience and segmentation data. Specifically, AI is the driving force that allows you to capture relevant data about campaign activity, such as the number of targets, who opened emails, who and how many people clicked the CTAs, visited the landing pages, or interacted with the website - all with the aim of better understanding your audience.
To that end, AI-driven marketing platforms can also help automatically generate uniquely personal content in the body of the email specific to individual users, with subject lines tailored to the person’s interests, profession, hobbies, and buying patterns. A hospitality company, for example, might send users personalized content that offers room deals and specials that suit their needs based on their demographic (e.g. families with small children, couples, senior citizens, etc..), as well as activities and sites that might be of interest to them if they stay. These kinds of highly personalized insights, in turn, allow you to create more targeted and relevant campaigns that will likely give a big boost to open rates.
In addition to personalizing content, marketers can now use AI-driven tools to both assess and improve the quality and effectiveness of their marketing campaigns, optimizing every step of the email campaign process at granular level, all the way down to the ideal time of day for sending an email to potential leads. What’s more, Artificial Intelligence gives marketers the ability to immediately access campaign results in real-time. This means that labor-intensive A/B tests with weeks-long analysis will slowly fade into a distant memory for marketers, who will instead be able to access relevant campaign data at the drop of a hat anytime they want.
Improved Ad Copy and Content Creation
Okay, so Artificial Intelligence can be used to analyze data, optimize campaigns and otherwise perform repetitive tasks, but can it actually be used in a creative capacity for ad copy and other content creation? The short answer: Yes.
While it still has its limitations, it can also be used for producing creative marketing content based on a plethora of inputs that include raw consumer information and specific targeting and segmentation data. AI-based tools, such as Articoolo and Quill, are already are being used to quickly and efficiently generate high-quality marketing content - including ad, landing page, and email copy. Among other things, AI can be used to create content that gauges audience relevance, produces engaging and compelling storytelling, or triggers an action or response. For marketers, this means they now have an enhanced ability to generate different types of content for a multitude of campaigns without adding resources to their creative team or investing in an external agency.
Whether informative blog posts, customer testimonial videos, or recorded webinars, in recent years, digital marketers are constantly generating new content in an effort to better engage and reach their target audience. Thus, as these solutions become more refined, it’s likely that marketers will increasingly rely on Artificial Intelligence to fuel content creation more quickly and even more creatively than ever before.
Reduced Ad Spend Waste
It’s no secret that Artificial Intelligence uncovers a dearth of new efficiencies that enhance productivity and boost ROI. And as such, one of the biggest benefits will be to significantly reduce ad spend waste.
The most obvious, of course, is its ability to optimize your campaigns and PPC strategy as a whole. AI-based tools can breathe new life into your PPC campaigns by providing:
But perhaps less known is that AI can also be crucial in identifying malicious bots and other types of ad fraud activities, helping marketers identify and avoid costly attacks before they occur while ensuring that their advertising dollars are only spent on real customers and genuine clicks and views.
Increased Conversions
It’s no secret that AI-enabled platforms have the ability to learn, analyze, and adapt -- all good news for marketers attempting to get a finger on the pulse of their audience. Now becoming a staple to digital marketers and advertisers, AI is routinely being used to uncover relevant product and brand recommendations, as well as offering tips to consumers at just the right time in their buyers’ journey. For brands, that means countless new avenues to create customer loyalty and build trust within their consumer base.
In addition to creating a better overall customer experience, AI-driven tools can even be the conversion funnel itself. Global beauty giant Olay’s skin care analysis tool, for example, leverages AI technologies to analyze customers’ skin, and then makes recommendations for ideal products that they can purchase based on their unique needs and individual tastes. From making recommendations about clothes to cars to the latest lawn care tools, the possibilities are just about endless.
Artificial Intelligence is already making waves in the digital marketing industry. While still in nascent phases, it’s already a critical component in a plethora of tools designed to boost PPC efficiency, ROI, and even creativity.
Safe to say, these are exciting times for marketers. As Artificial Intelligence progresses in its sophistication and acceptance in the industry, marketers will be uniquely positioned to access new ways of reaching and connecting with their audience. The scope of AI’s innovation is only going to expand in the months and years ahead -- and for marketers, now is the perfect time to find ways to leverage its vast potential to make their marketing efforts faster, more efficient, and more profitable than ever before.
Your paid and organic marketing efforts are doing the business -- click-through rates, or CTRs, have never been higher and record numbers of visitors are finding their way to your website. Time to put your feet up and stick the kettle on? Not so fast. If that traffic isn’t converting, all of your hard work has been for nothing. Whether you are just starting up and running the show solo or if you are a seasoned marketing director who has signed up to some pretty ambitious KPIs, optimizing your webpages to increase conversions is plainly a must.
Naturally, every online marketer will measure successful conversions differently based upon their business model and specific goals. Across all verticals, conversions are expressed simply as visitors who perform a desired action: for an online publisher this would be the submission of a form on a subscription page; for a digital retailer this would be the addition of products to a cart. However, whatever industry you’re working in, a 2% conversion rate should be the baseline goal for your website: reaching this number and beyond is the very foundation of high sales volume. In this article, we outline four tried and tested tactics that, if put into practice effectively, will be sure to get you the conversion percentages you covet.
On search engine real estate it’s all about gaining prime location for your ads. When it comes to optimizing conversions, it’s all about continuous testing. The nature of experimentation by definition dictates that some tests will succeed and some will fail: either way, both outcomes represent great learning opportunities. It is the best way to mitigate the risks that come with decision-making while simultaneously affording your creative teams room to do what they do best - design, discover, innovate, explore.
The first step of any meaningful test is to study the statistics and data available to you to isolate an element that has the potential to improve customer engagement. Speaking generally, some components on a webpage tend to have higher effects on conversion rate and numbers than others, so begin by focusing on these things:
The headline
Are you getting your message across instantly? Is it providing immediate and easily digestible value?
Page design
Are you packing a visual punch? Are your images streamlined, easy on the eye, and independently adding value?
The offer
Take a step back and consider what the customer is getting for their money. How is it presented? Is the information on the page still relevant? Is the message conveyed clearly?
Call to Action, or CTA
Does it guide your visitor to the metaphorical finish line? Is it concise and synthetic?
Testing should be a never-ending process. As soon as you’ve optimized one aspect of your webpage, shift attention and build out variations of something else. The more you integrate A/B and multivariate testing into your core marketing strategy, the more your decisions can be influenced by real-time data rather than ideas and opinions. If you’re leaving things to chance, you’re leaving precious dollars on the table.
A common mistake among digital marketing practitioners today is that they do not provide a distinct and compelling value proposition up front. If your homepage or landing pages are simply dominated by your logo or ineffective “welcome” messages, you are missing out. The importance of nailing your core messaging cannot be overstated in the environment of saturated online marketplaces -- while you are likely to match your competitors in a number of ways, you need to outperform them in certain key areas and sell that to your prospective customers.
Of course, crafting and refining your value proposition is a facet of your business that goes far beyond the pages of your website -- it is the very essence of what you stand for and what you do. It requires reflection and a constantly open dialogue both internally and externally. But once it has been defined, it must be communicated efficaciously in order to achieve optimal results across your entire organization -- from marketing to sales and everything in between. Ideally, your value proposition should be articulated in a single, credible sentence that leaves no space for ambiguity. However well-defined and eloquently expressed you think it may be, though, to understand its true resonance, you must be repeatedly measuring how it performs (scroll back to point number 1). While many marketers first look to things like font size, button shapes, and other elements to tackle lagging conversions, the first step has to be analyzing the value you are communicating.
For anyone to part ways with their sensitive data by filling out a form, or their money through a purchase of a product or service, they need to feel confident in your brand and secure in the transaction. One of the most straightforward ways to boost conversions is to make it easy for the visitor to verify the accuracy of your content through articles in renowned publications, citations, reviews and case studies. We’ve all seen the traditional before-and-after type testimonials -- when done well they are an extremely effective marketing tool, triggering emotional responses in viewers and providing tangible examples of just how consumers can benefit from your offering. The effects of such endorsements have been the source of great industry debate, with some reports suggesting that the inclusion of videos on landing pages will increase conversions by a massive 80%. That is a compelling number and certainly justifies giving it a go if you’re not already.
While the above would undoubtedly be part of your long-term strategy -- video testimonials are not cheap or easy -- there are some quick fixes around your website that you can implement to build credibility. Start by listing a physical address, showcasing photographs of your offices, listing your affiliations with respected organizations, displaying biographies of your leadership team, and making it easy to get in touch. Then take into consideration the navigation and ease-of-use -- nothing kills trust quicker than an outdated, amateur-looking website. When constructing your webpages, be sure to update all of your visible content, remove any peripheral distractions (pop-ups, blinking banners, etc), stay consistent, and avoid errors of any kind. You’d be surprised just how many seemingly minor things can hurt your credibility.
Now this sounds like a given, right? But again, you’d be amazed at the number of companies who make doing business difficult. In short, your visitors should not have to figure out how to sign up, buy, or where to click -- the desired action should be apparent. On every page that contains a CTA, everything should be geared around guiding the user toward the action you want them to take. If it’s a sign-up, ask them to fill in as few fields as possible -- don’t ask for any information that you don’t need to know to complete the process. If it’s a product order, don’t bombard them with similar offerings that can detract attention and do not force guests to sign-up before checking out.
You should also keep in mind that regardless of the quality of your offering or your webpage, there are always going to be visitors who are not quite ready to make that all-important click. To keep these visitors engaged, consider providing a second CTA. In addition to saving those potentially lost conversions, they’re great for progressing leads through the funnel and supporting other company goals that could involve social sharing or signing up for company updates.
Every visitor comes to your website for a reason - most likely because they clicked on an ad or an organic search result that they liked or was appealing. Each of them arrives with wants, needs, and expectations. Displaying value out of the gate, building up trust and encouraging conversions through simple navigation are the basic strategies you can employ that will ultimately compel your audience to take action. Getting traffic to your website is one thing, but getting that traffic to convert is another thing entirely. And understanding the difference is the key.
A growing number of agencies are radically transforming their businesses by equipping their media buying teams with a robust digital media platform. Centro has guided hundreds of digital marketing leaders and media teams on what to look for in a Demand Side Platform (DSP), and the first thing to note? You need more than just a DSP.
In this January's webinar, we helped to solve the puzzle of selecting a digital media platform by breaking it down into 10-steps and sharing key considerations and questions for potential vendors.
No two businesses have identical goals and targets, and as such, choosing what we want to measure should be done with care. If we incorrectly set our business goals and track the wrong metrics, we are essentially playing a high-stakes game with the wrong rules.
With automated bidding platforms, selecting a metric is even more paramount. An automated platform will happily optimize toward the metric chosen for it, regardless of how appropriate it is to the company’s business goals.
To ensure we choose the right metrics going forward, we will go through some of the common pitfalls, discuss how to determine the goals for an online advertising campaign, and consider a hypothetical case study that applies these new rules.
Some of the most common mistakes when defining metrics include choosing vanity metrics, measuring what is convenient, and measuring the wrong part of the sales funnel. We’ll go into each.
Vanity Metrics
Vanity metrics, as you could probably can tell from the name, are the kind of metrics that are easy to measure and increase, but don’t tell you anything about the underlying process for the business goals you are trying to measure and improve. These kinds of metrics have been discussed quite extensively elsewhere -- entrepreneur Tim Ferris describes them as “the easiest to measure and they tend to make you feel good about yourself.” Another entrepreneur, Neil Patel, defines vanity metrics as “all those data points that make us feel good if they go up but don’t help us make decisions.” In short, vanity metrics are easily gamed, but changes to them will likely not result in noticeable changes to the underlying business goal.
Here’s an example -- imagine a soccer team that only measured success by the number of passes they completed in a game. Sure, there is probably some relationship between the amount of time they had the ball and how many goals that team scored, but in reality, optimizing toward passes would likely lead to a lot of wasted time with the ball, racking up a large number of passes with no intention of putting the ball in the back of the net -- which is ultimately the underlying team goal.
Similarly, an example of a commonly used vanity metric when optimizing online advertising campaigns is click-through rate. For example, if a company’s main business goal is to sell as much product as possible, and the percentage of clicked ads increases, then we should see more sales, right? Not so fast. Click-through rate can be changed by many factors - a decrease in Ad Views would result in an increase in click-through rate, but for a reason that does not necessarily affect the number of people on the site who end up buying a product.
Despite these drawbacks, metrics like these still have their uses -- often as a supplementary measure to help explain changes in the main metrics you are optimizing.
Measuring What is Convenient
As with vanity metrics mentioned above, there is also often a bias to choosing goals based on metrics that are easily available to us. Often the conversion data currently being recorded in an analytics platform is sufficient to measure our business goals, but occasionally additional integration will be required to pull data from another source.
For example, you may include leads and conversion metrics in your analytics software, but revenue data may be ‘stuck’ in your CRM or accounting software. If you were attempting to maximize profit, the ‘convenience metric’ would be conversions.
Measuring the Wrong Part of the Sales Funnel
One area where metrics are often poorly used is when targeting the wrong section of the sales funnel. Making this mistake typically comes from an error in understanding the relationship between each section of the funnel, and the characteristics of visitors to your website or online store. There are often underlying characteristics of the populations in each section of the sales funnel that we can’t see or that aren’t immediately obvious -- and optimizing toward higher sections in the funnel do not necessarily increase the number of leads in lower sections of the funnel, which is typically where revenue is recorded.
To help understand the process of determining the metrics that require optimization, we will go through a simple hypothetical situation, and explore how we would choose the appropriate metrics to track.
Example: Online Florist
Imagine an online florist that offers two types of plants - a cheap bouquet of flowers, and an expensive potted plant. The owner cares about one thing, maximizing their total revenue. The store currently records Ad Views, Ad Clicks, Site Views, Orders, and Cost for each bidding keyword in their analytics program. The store’s accounting software records Revenue data for each sale, but the team has put off integrating that data with the analytics program.
How would we go about selecting a metric to optimize toward the owner’s business goal?
First, let’s identify some potential metrics that would come under the common pitfalls discussed earlier. Ad Views, Clicks, and Site Views -- while they are all a good idea, increasing these will not directly help us with our business goal of maximizing Revenue.
It seems as though Revenue is the best metric to optimize toward, but it is not available to us without some integration work. However, the Orders metric is easily available to us, and is similar to Revenue - is there any harm in using it instead?
Actually, there is. With this simple example, Orders conversions come from one of two populations - either the low-revenue bouquet customers, and the high-revenue potted plant customers. If we only try and maximize the number of Orders that occur in the online store, we lose sight of our true goal of maximizing Revenue, as each Order has a different Revenue value attached to it, and our analytics platform has no way of knowing that value.
With an automated bidding platform, this distinction between Orders and Revenue is even more important. If we were to let an automated platform optimize toward increasing the number of Sales, a likely result is that bids for keywords such as “cheap bouquet” will increase, and bids for keywords such as “fancy potted plant” would decrease. This is because the algorithm does not know the ‘value’ of a given Order, as the Revenue data is hidden from the algorithm’s view. As such, this would likely result in an increase in total Orders, but possibly a decrease in total Revenue, as potential customers looking for cheap flowers are less expensive to target compared to those wanting to spend a lot more money on a fancier plant.
As such, the recommendation here would be to integrate this Revenue data into the store’s analytics program, and optimize toward the Revenue metric instead.
The florist case study was a very simple (and somewhat contrived) example, but the process in understanding what metrics to choose does hold when applied to real-world business goals.
Each business is different, but being conscious of the pitfalls that might occur when optimizing toward vanity metrics, convenient metrics, and metrics that are targeted at the wrong level of the sales funnel will go a long way toward improving your online campaigns. Doing so ensures that you are measuring what matters, and that you can be confident that hitting targets with your chosen metric will actually result in improved business performance.