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The Easiest Guide to Cohort Analysis

Cohort is a group of users experiencing a common event within the same time period. An oft-repeated but very relevant example of a cohort is- a group of students joining in the same year. So the class of 2017 is a cohort and so is a class of 18, and so on and so forth. What is cohort analysis? Cohort analysis is an analytical modeling employed to study the cohorts characteristics over a period of time and the elements that influence change in those characteristics. It traces its roots to medical research where cohort studies are done to identify the cause of a disease. “In a prospective cohort study, researchers first raise a research question, forming a hypothesis about the potential causes of a disease. The researchers then observe a group of people, the cohort, over a period of time (often several years), collecting data that may be relevant to the disease. This allows the researchers to detect any changes in health in relation to the potential risk factors they have identified.” via Medical News Study So, to identify the cause of lung cancer doctors would create a hypothesis that it is caused by smoking. Then they will take two groups- smokers and non-smokers. Thereafter, both groups would be studied to identify the influence of smoking on the person’s likelihood to get lung cancer. How do we employ this in business analytics? In business applications, we compare cohorts- users sharing a common experience in a given time frame- or analyze the behavior of a single cohort, to identify a pattern that supports a growth hypothesis. That hypothesis could be anything. For instance, we may create a hypothesis that users getting acquired via display ads have higher LTV than the ones getting acquired by Facebook. To prove the hypothesis we would do the cohort analysis. Likewise, let’s suppose we want to identify the cause of the aggregate dip in your retention.So we would form a hypothesis that retention has a correlation with the first purchase of the customer. To establish the relation we shall cohortize users on the basis of their first purchase and plot their, say monthly, retention %. From the graph above it is apparent that the users who purchased marshmallows the first time displayed higher LTV than the others. This despite the fact that overall retention of the product has declined. Naturally, the intent of business now would be to get more users purchase marshmallows post acquisition. Important- That’s not to say that Marshmallows are the cause of retention. Our analysis simply told us that there is a correlation between marshmallows and retention. Correlation doesn’t amount to causation. So we have to test if Marshmallows really amount to higher retention or not. Cohort analysis gives us insight into the trend and basis for testing. Not the cause. Cohorts and Segments are not the same Most folks interchangeably use ‘Cohort’ and ‘Segment’ which is not correct. For two users to be part of the same cohort they have to be bound by the common event and time period. Eg 2017 graduates, 1990 born men. However, to create a Segment you could use almost any condition as a basis which cannot necessarily be time and event based. Eg graduates, men. Cohort is a subset of Segment. So, there can be a cohort of ‘new users this week’ and likewise, there can also ‘segment of new users this week’. Now that we have understood fundamentals of cohorts, let’s understand some business use-cases. Some powerful use-cases of Cohort Analysis To explain the use-cases start with the google sheets (linked below) where you can start with the cohort chart for every use-case. Cohort Analysis | Worksheet 1. Understanding customer retention But before we do that, a little throwback to how to read a cohort chart. We are skipping the data crunching part and jumping right into the presentation. How to read a cohort chart? Table 1 Link- Cohort by Active users- Sheet 1 | Excel Let’s go through row and column one by one. You could well see that column is for activation month and row is for the number of returning customers. Rows So, B4 represents the number of new customers we acquired in the month of Jan. C4 tells us the number of customers who were acquired in Jan but they returned in Feb. Likewise C4- number of customers acquired in Jan who returned in March. D4- the ones who returned in April And so on and so forth. Basically, as we move along the Jan’s row. we understand how the retention of new customers acquired in Jan fluctuated until Dec. Columns Column represents the number of returning or new customers. D4 represents the number of customers acquired in Jan who returned in March. D5- the number of customers acquired in Feb who returned in March. D6 is the number of new customers acquired in March. The same pattern repeats as we move along the row. Table 2 Now, let’s understand how the each cohort, retention wise, behaves over the period of time. To do that, we would slightly pivot the above table. We would change the column from the actual month to the ‘# of months since acquisition’. From Jan, Feb to 0. 1, 2 which would pull all the row data to the left. You may notice that the table changed from right aligned triangle changed to left aligned. So, in the first row, as we move along, we would know how many customers acquired in Jan returned in the succeeding months. Table 3 In this table, we changed the numbers into percentage to get better view of the data. Now looking at each row we may get the retention curve of the corresponding month. However, what if we want to understand how the retention has been over the past 12 months? So, in the final row, we have calculated the aggregate. The aggregate gives us the retention curve of the past 12 months. 2. Correlation between category and retention A friend of mine had worked on the cohort analysis of one of the world’s largest retailer. He told me that one of the conclusions from their analysis was that the users who purchased baby products in their first visit showed higher propensity to visit again. This prompted the retailer to promote their baby section more aggressively. One can create a hypothesis that there are some categories which trigger maximum stickiness among users when they are the first purchase. To determine that category let’s cohortize users on the basis of category of their first purchase and plot their retention. Link- Cohorts by Category- Sheet 2 From the chart it is evident one can draw the following conclusions: Users buys Sportswear in the first purchase showed higher retention than the rest. Users buying Jewelleries in the first purchase showed the lowest retention rate. 5th month is critical as the churn seems to increasing beyond that. Some possible inferences can be that the marketing expense for sportswear needs to be decreased. Likewise, the retention strategies for Jewellery purchasers need to be relooked. Retention strategy for users entering 5th month since their acquisition has to be evaluated. 3. What features correspond to maximum retention A report by Quettra shows that an average app loses 77% of the DAUs within 3 days post install. Now, if your product itself isn’t deserving, then nothing can evade uninstall. However, if it is not, then apparently the first three days are critical and determinant of the user’s retention. 3 days was the average trend and your critical number could accordingly vary. You could determine your own critical number through the method that we discussed in #1. Let’s suppose it is x days for the time being then you have to do something within the first x days post install to hook users. How cohort analysis comes into picture Let’s create a hypothesis that there are some features in the app which when used increases the stickiness among users. Create an aggregate retention curve of the last 12 months like we did in #1. Note- The retention curve of the mobile app unlike a web-app is going to decrease linearly because a web-app doesn’t need to be installed on your device. A user can login any time he wishes. With mobile app, once it is uninstalled you potentially lose the user forever. Now, screen the users who have retained and jot down the features used by them on the first day. Suppose you are analysing for a e-commerce app and concluded the following traits to be common among all retained users. Let’s say “push notification clicked” and “added to wishlist” are two most common actions Now we would narrow our analysis for both of these events and do a comparison between them The result Cohort Analysis | Cohort by Features Visit the above sheet and change the value for each feature from the drop down to see how the graph changes. From the above chart, it would be clear that users who added-to-wishlist display higher propensity to retain than the rest. The ones who clicked push notification perform even worse than the average. Again, this graph gives us the correlation not the cause of retention. P.S. This is a very interesting method and extensively used by consumer businesses. I just discussed the basic framework and there are various edges that can lead you to a more definite conclusion. 4. How customers react to a new feature release Inversely the above cohort analysis could also be used to figure out what are the obsolete features that needs some rework. For instance, the cohorts curve of users who clicked on push notification fare poorly than the average retention curve. Push notification is obviously meant to complement your retention so the above chart prompts us to rethink our strategy. Creating cohorts in Mixpanel, Amplitude, Adobe- First event and Returning event If you are using Amplitude or Mixpanel, or any of the similar products, to do your cohort analysis, these are the two fields that you have to specify for creating cohort chart First event Returning event Let’s see some examples Amplitude Mixpanel Adobe Localytics First event is the primary criteria to build the cohort- the ‘experience’ element in creating cohort that we discussed in the very beginning. Returning event is the baseline that you want to track for your users. In the above charts, retention has been the baseline of our analysis. In analytics, retention could be defined as ‘any event performed by the user’ on your platform. So, if we have create cohort in Amplitude then it would somewhat look like this Conclusion Cohort analysis is a respite from vanity metrics. At any time momentary growth can be bought which may give you temporary pleasure but cohort analysis allows to be cynical. It gives a very critical view of churn and doesn’t let it get masked by growth. For instance if you are investing into acquisition there can be instant surge in the MAU but high MAU is not the indicator of growth. A cohort analysis will tell how many of those acquisitions are actually sticking with you. Similarly, a particular channel might be amounting to highest acquisition. But a cohort analysis will tell which of them contribute to maximum profit. Whatever your key metrics may be you would be able to see how it evolves over the customer lifecycle or product lifecycle. Source:


Customer Lifetime Value in Ecommerce

For any company to be profitable, it must profit more from each customer (Customer Lifetime Value or LTV) than it spends on acquiring them (Customer Acquisition Cost or CAC). So if your average Customer Lifetime Value is lower than your Cost Per Acquisition, that should be a big point of concern for your company because it means that you are losing money. Being unable to maintain Costumer Acquisition Cost lower than Customer Lifetime Value is one of the main causes for business failure. How to calculate Customer Lifetime Value Lifetime value is how your store profits from your clients during the time they remain customers. For example, if your average client comes back to your store three times to buy something, spends on average $100 per purchase and your profit margin is 10% ($10), your Customer Lifetime Value is $30. This is important because LTV is directly linked to profitability, since a company with high LTV will be able to spend more to attract customers and will have a higher margin. To estimate LTV, you need to look into your historical data and: Forecast the average customer lifetime (or how long the customer continues to purchase your product or service); Forecast future revenues, based on estimations about future products purchased and prices paid. Estimate the costs of distributing those products. Calculate the net value of these future amounts. Famous best practices in Retention and Customer Lifetime Value Companies that have high Retention (their customers keep coming back to shop more) are more successful because their Customer Lifetime Value gets higher. For example: Zappos won against their competition by keeping their customers coming back with an excellent customer service strategy. The more often they buy, the higher Zappos’ LTV gets. Amazon’s massive product offerings helps them in upselling or cross-selling to nearly everyone using an automated and personalized email marketing system. This means users spend more, which in turn improves Amazon’s LTV. Netflix’s recommendation system keeps viewers constantly engaged in new content. Netflix’s customers keep their subscriptions for a year or more, paying every month, which increases LTV. Facebook “habit loop” keeps their users coming back to the site on a daily basis (and often, multiple times a day). When users visit Facebook more often, they tend to click more on ads. Since Facebook profits from each ad click, this greatly improves their LTV. Why the ratio between CAC and LTV is crucial for running your business Customer Acquisition Cost (CAC) is calculated based on the amount of money you spend to acquire a customer. For example, if you pay $1 for each click that a person makes on your Facebook Ad and 1 in every 10 people who click on that ad ends up buying from you, your CAC is $10. Considering the example above, of a company who’s Customer Lifetime Value is $30, if their CAC is $10, that means their profit is $20 per customer. A $20 profit is not so bad if your company has a high volume of sales. However, if that company’s clients came back to shop at an average of 10 times, their LTV would be $100. If the LTV is $100 and the CAC is $10, then the final profit would be $90. Which is obviously much better. If you’re currently running Facebook Ads or any other paid marketing channels, you’ll appreciate how difficult it is to keep Costs per Acquisition down. So it’s in your interest to keep Customer Lifetime Value as high as possible. And the secret for keeping LTV high is retention. See below: How Retention Rates impacts Customer Lifetime Value The first example is of a company struggling to retain their customers. The second shows a business with high retention rates. The graph below demonstrates the retention curve of a company with only 30% of their customers returning in the next month. You can see that they end up with almost zero customers from each cohort in less than 5 months: Low retention rates result in Customer Lifetime Value barely increasing over time. Companies with low Customer Lifetime Value can only really count on one purchase per customer to draw all of their profits. If a company has low Customer Lifetime Value, average CAC needs to be below average to profit from each customer. On the other hand, the company represented in the next graph has a subscription based model. They maintain a much higher retention rate. More than 20% of their users are still active after 18 months from their first payment. That reflects very positively in their Customer Lifetime Value, as we can see in the graph below. Even though revenue from their first purchase is low, in the long run each customer becomes extremely valuable because of the high retention rate. Whatever the case and the market you are in, a low LTV / CAC ratio is a problem that should be addressed as soon as possible. If that’s a problem you have,  we strongly encourage you to your Retention after the first transaction. Conclusion For many young businesses, keeping a healthy CAC / LTV ratio is a challenge. If that’s your case, you need to identify whether your CAC is high or your LTV low (or both). Benchmark your numbers against your competition to understand which of them is your biggest problem. Then divert all of your focus to getting it fixed. If the problem is retention, you have a few different options to test: Focus on customer satisfaction by providing an excellent experience with your product. Build a recommendations engine and an email automated system. Use them to personalize the offers to your customers based on their activity with your site or app. Work on developing a habit-forming loop to insert your product in the daily routine of your users. Or you can look at your own data and come up with your own strategy. The important thing is to focus on your CAC / LTV ratio immediately. The lifetime value of your company depends on it. Source:


4 Steps for Effective Customer Acquisition in the Digital Era

It’s no secret that acquiring new customers is difficult. While most companies work to derive as much value as possible from existing customers–which they should—your business will have a tough time reaching its growth goals if new customers are never brought into the fold. In the digital era, customer interactions occur online, and in shorter, more frequent stints, rather than the longer in-person, but less frequent, interactions of old. Likewise, traditional marketing meant focusing on customer segmentation and campaign performance measurement. That no longer works. Instead, the focus needs to be on individual preferences and intentions. Not doing so can lead to missed opportunities. There are several factors to consider in your customer acquisition strategy, and they all come down to an explicit focus on the customer: details such as understanding how (and why) individuals interact with each channel differently, recognizing how to leverage multi-channel data to connect with the right customers at the right time, and respecting that customers want to be treated as individuals. To win the battle for new customers, companies must continuously leverage digital technologies to attract new customers and connect in a relevant, meaningful way based on the prospect’s individual preferences. Here are four key steps to acquire new customers in the digital era. 1. End the Siloes  Your business can’t be effective with your consumer interactions if you’re working with data that is in siloes. Marketing teams must know and understand information around sales calls, online behavior, marketing program feedback, etc., to make the most of each marketing campaign and next best offer. These make up an ongoing cycle of events that contribute to a personalized understanding of the prospect or consumer. Having a holistic, real-time view is the only way to be relevant and effective in your marketing efforts. 2. Detect Opportunities Pinpointing new opportunities at the prospecting stage will allow your teams to allocate resources in the areas that will have the most impact. Signals of intent – like multiple visits to your website – need to be merged and used during the acquisition process as quickly as possible. Typical prospect journeys will become visible and can be mapped to other prospects, all the while improving acquisition. You want to be able to compare past activities of the customers you have acquired and apply those behavioral patterns to new prospects to gain a better understanding of predictive behavior. This can help you make the right offers to transition the prospect into a customer. 3. Turn Insight into Action  Detecting an opportunity is not enough on its own to improve customer acquisition; you need to process that opportunity as quickly as possible and use the most appropriate channel to connect with that prospect while the opportunity is still there. That process can be a call by the sales team, but it can also be a digital interaction – an email, online banner offer or other digital conversation, depending on the profile of that customer. The key is delivering the right message that will resonate with that particular prospect based on the behavioral, contextual data mentioned above. 4. Test Multiple Strategies  If you’re in a rut, it’s beneficial to engage prospects with different marketing messages and track response rates to learn what’s working and what’s not. Being able to track and change based on individual behavior patterns will allow you to improve your customer acquisition tactics. Delivering the right message via the right channel at just the right time is crucial, so despite the number of ways in which we can reach prospects, if we haven’t carefully considered what it is they want or need, or how they want to hear that message, we likely won’t get very far. Instead, companies that embrace a customer-centric approach include customer-focused concepts in their entire makeup. “Personal,” “thoughtful,” “anytime, “anywhere” – these are requirements for growth in the digital era and impacting the customer acquisition process. It may take some trial and error, but a successful acquisition strategy is all about committing to better understanding your customer—at all stages of engagement and via a variety of digital channels—and building personalized relationships with each. Source:


7 Predictions For The Shape Of Content Marketing In 2020

Wait a minute, isn’t it only 2017? You’re right, and 2017 is shaping up to be a big year for content marketing, but as fast as technology develops, it still takes a few years for trends to really take form. Google Glass seemed like a big deal at the time—until it wasn’t, and smart watches never grew to become the market dominators they were once forecasted to be. At the same time, I remember seeing the flurry of posts calling for the death of SEO at the arrival of the Panda and Penguin updates, which played a major role in shaping SEO (but never came close to killing it). So rather than taking a stab at the immediate repercussions and developments that may tweak your content marketing strategy this year, I want to look further into the future, where these trends and technologies will have had more time to manifest, so you can prepare for the bigger disruptions to come: 1. Augmented reality interactions. Augmented reality had a big year in 2016, with Oculus Rift, Pokemon Go, and the announcement of Snapchat Spectacles (among other tech developments). But it’s still not popular or widespread enough for it to be categorized as a viable medium for content marketing. But now, all doubts about the technology’s future have been squashed, and brands will be racing to be among the first to leverage this new medium for their own purposes, whether that’s interactive advertising or new experiences for in-person customers. 2. A reshaping of SEO. Unless you’ve been centering your business on an Amazon store or a similar eCommerce platform, most of your SEO efforts revolve around your website. This seems both intuitive and obvious; search engine results pages (SERPs) are basically giant lists of web pages, so the more visibility you get there, the better. However, we’re starting to see different kinds of entries in SERPs, and less exposure for websites in general. Knowledge Graph entries and rich answers are replacing traditional site entries, apps (including streaming app content) are rising in relevance, and of course, our digital assistants are parroting answers to us, eliminating the need to review an SERP. As these trends develop, users will still rely on search, but they’ll use it in entirely new ways—and the importance of website-specific optimization will begin to decline in favor of things like app SEO and optimization for rich answers. 3. Live video dominance. Live video’s popularity isn’t exactly a secret, but there’s one thing holding it back from being a dominant form of content on the web: participation. Live videos, when available, attract a lot of user attention, but not enough brands have jumped on the trend. Part of this is due to the amount of planning necessary for a “successful” feed, and mobile data plans and Wi-Fi reliability may also enter into the equation. But by 2020, my guess is live video will stabilize as an available means of communication, and we’ll see it in higher demand and in more places—including search results. 4. A native advertising surge. People hate advertisements. They’re tired of being bombarded with ad messages, they don’t like the idea of being persuaded, and they resent the big businesses that are trying to take their money. That’s why native advertising, which I view as a hybrid of traditional advertising and content marketing, is likely to constitute the majority of ad revenue online by 2020. Even traditional forms of advertising will work harder to “blend in” with the type of content that users expect to see in a given medium. 5. Content length extremes. Currently, there’s a wide range of different-length content that can become popular. Short, medium, and long posts all have advantages and disadvantages, with long posts attracting more links, and short posts spreading faster and requiring less investment. By 2020, I imagine we’ll see more polarization toward content extremes; people who want deep, long content will want the deepest, longest content they can find, while anyone who wants a fast read will only consume content in bite-sized chunks. This will force most content marketers to rethink their direction, optimizing for one style over the other. 6. Higher social value. We’ll also see a spike in the social value associated with the content we produce and share. Authorship is currently important, and influencer marketing yields fantastic results, but as corporate distrust grows and internet accessibility widens, it’s going to be even more important to know—personally—who you’re getting your content from. Individual personalities are going to make or break brands, and the value of a post can increase exponentially based on who writes or shares it. 7. Personal device interactions. Voice search has exploded in popularity over the past five years or so, mostly because algorithms became good enough to actually understand what we’re saying. But we’re now starting to interact with our devices in new and uncharted ways; we’re having real, back-and-forth conversations with them, eliminating the need for screen-based or type-based interactions. By 2020, I believe this will give rise to new types of content that aren’t screen-based; podcasts are an interesting start, but in the future, more conversational, interactive forms of content will be in demand. Though some of these predictions are speculative, the majority of them are end-game visions of trends that have already begun. If you have a good rhythm, it’s a good idea to maintain it; there’s no use scrapping your strategy and rebuilding from scratch for concepts that are only now coming into fruition. Still, it pays to think ahead; the most successful content marketers tend to be the ones who beat their competitors to market, so there’s definitely a value in early adoption. Source:


Using Advertising Landing Pages to Nurture Customers

Like a rose is a rose is a rose, your brand is your brand is your brand. Think of it like this. Your brand is like a delicate flower. It is something you’ve cared for, cultivated, and grown into an entity that represents everything you, your team, and company wishes to share with the world. That’s why you’re proud of your brand, and why it’s upsetting when it goes unnoticed. There are many ways to draw attention to your brand and one of the best is to utilize landing pages. Landing pages make a lasting first impression and are ideally suited to creating powerful, personalized ads that fully convey all the awesomeness that is your brand. An advertising landing page politely ushers your potential customers the duration of the customer journey, so it’s crucial to recognize that every promotion or ad needs its own landing page. In this post, we’re going to examine how good advertising landing pages move potential customers through each step of the buying cycle and help your brand get the attention you know it deserves. What is an advertising landing page? An advertising landing page is a standalone web page that visitors are brought to from various forms of advertising channels. Advertising landing pages are designed to convince visitors to convert on a specific offer (to buy a product, download an ebook, register for a webinar, etc.) by using persuasive elements like compelling headlines, benefit-oriented copy, engaging media, and customer testimonials. Advertising landing pages can, and should, be utilized throughout the marketing funnel to make the buyer’s journey meaningful and effective. How are brands using advertising landing pages at each stage of the buyer's journey? Brands are using advertising landing pages at each stage of the marketing funnel to optimize the buyer’s journey. This practice provides brands with the ability to raise brand awareness, drive traffic, and increase sales. Take a look below at how content fits into the buyer’s journey at each stage. These are not exclusive to their respective stage, but are often bucketed this way: Let’s briefly review each stage of the marketing funnel, and examine how brands are using advertising landing pages to achieve success throughout the buyer’s journey. We’ll also discuss elements that should be A/B tested in order to potentially achieve better results. Keep in mind, for shorter pages, we’ve shown the entire page. However, for longer pages, we only displayed above the fold. You may need to click through to each page to see some of the points we discuss. Also, ome brands may be A/B tested their page with an alternate version than is displayed below. In the awareness stage The awareness stage is the beginning of the buyer’s journey; before someone knows anything about your brand. The prospect knows that they have an issue, and that the issue needs a solution but they don’t have any idea how they’re going to solve the issue. In the awareness stage, landing page advertising is typically for educational, editorial, and expert content, analyst and research reports, tip lists, ebooks, white papers, and blog subscriptions. Boldchat Boldchat is one brand that uses an advertising landing page in the awareness stage of the buyer’s journey. The following AdWords ad and landing page was found by searching the term “improve user experience” and is used to generate playbook downloads: What the page does well: The headline is attention-grabbing, both aesthetically and with the compelling copy. Numerical statistics about customer experience help persuade prospects to download the playbook to learn more about how they can improve their own customer engagement. The image gives prospects a preview of what they’ll receive by downloading the playbook. Bullet points with personalized copy let prospects know what they’ll learn from the playbook and how it will benefit them. The “Start chat” button on the right side of the page allows prospects to contact the customer service team without exiting the page. What could be changed or A/B tested: Exit links (the company logo and social links) could reduce conversion rates by providing prospects with a way off the page before downloading the playbook. 7 form fields is a bit high for a landing page in the awareness stage of the buyer’s journey. At this stage of the game, the company shouldn’t need so much information. The CTA button copy is vague and unpersuasive. Something more exciting and benefit-oriented like, “Get Engaged!” would likely persuade more prospects to convert. Adding white space around the most important elements, like the headline, form, and CTA button, would make them more attention-grabbing, and make the page look more organized. Analogous colors (red, orange, and yellow) make it so that no one color stands out too much. Changing the color of, say, the CTA button would make it “pop” off the page more. Too much variation in font style, size, and color makes the page look messy and difficult to comprehend. Akamai Akamai uses this AdWords ad and landing page (found by searching the phrase “page speed issues”) in the awareness stage of the buyer’s journey to generate free report downloads: What the page does well: Using “Free” in the headline is smart since people are more likely to redeem free offers than paid offers. The click-to-play video is informative, and is only 1-minute long, so it won’t bore prospects or prevent them from watching due to lengthiness. The encapsulated form serves as an implicit visual cue, drawing attention to the form so that prospects are more likely to complete it. Bullet points tell prospects what their report will contain, adding an element of persuasion to the offer. What could be changed or A/B tested: Too many form fields may deter prospects from completing the form. All of the requested information isn’t necessary in the awareness stage of the buyer’s journey. The CTA button copy could be improved. There is nothing engaging or convincing about “Submit.” Something more personal and descriptive like, “Send my report now!” may result in more leads. The CTA button color could be changed to a more contrasting color in order to make it stand out on the page. Exit links (company logo, navigation in the footer, etc.) give prospects a chance to leave the page before converting on the offer. The video advertises other videos at the end of it, which also increases the chance that prospects will leave before submitting their request for the report. Adding testimonials from customers who have already received the report would likely help to persuade others to convert on the offer as well. In the consideration stage The consideration stage is where the prospect begins to research all of his or her available solutions in the marketplace, and they have identified your company as a possible solution to their problem. As the prospect’s research becomes more in depth, he or she learns more about your knowledge, professionalism, authority, and trustworthiness and they are able to narrow down their list of potential choices. Advertising landing pages in the consideration stage offer content like webinars, free samples, guides, webcasts, and podcasts. LinkedIn Here is a LinkedIn PPC ad discovered by searching “marketing software guide”: Upon clicking the ad, I was brought to this landing page that LinkedIn uses in their consideration stage to persuade prospects to download their B2B Marketing Guide: What the page does well: Message matching is used with the ad and the landing page, as both advertise $50 in ad credits. Bullet points with bold font make it easy for prospects to find out what they’ll be getting and learning about with the guide. The auto fill feature on the form makes it faster and easier for prospects to complete it, increasing the chances that they will. Although having two of the same button seems like a mistake. What could be changed or A/B tested: The CTA button copy, “Download Now,” is vague. Something more engaging and enticing like, “Get the guide and $50 now!” may produce more leads. The CTA button color could be changed to a more attention-grabbing color (one that’s not used elsewhere on the page). Iconography with links to other landing pages is unnecessary and potentially decreases the conversion rate on this page. Instead of including the links on this page, each offer should have its own ad campaign and its own landing page. Exit links (company logo, header and footer navigations, social links) provide prospects a way off the page before downloading the guide. Adding customer testimonials from those who have already downloaded the guide and had success with it would likely convince others to download it as well. ReadyTalk Upon conducting a Google search for the phrase “content marketing webinar,” I came across this AdWords ad and landing page from ReadyTalk, encouraging prospects to sign up for their webinar: What the page does well: The image of the man adds a human element to the page, making the offer more relatable and enticing for prospects. Minimal copy is good, but adding personalized wording like “you” and “my” would be even better. The arrow above the form acts as a directional cue, telling prospects that there’s more to see beyond this landing page. The one-field form is fast and easy for prospects to complete, increasing their chances of doing so. No exit links (aside from the second CTA button mentioned below) means more prospects will stay on the page long enough to convert on the offer. What could be changed or A/B tested: “Webinars for the Customer Journey” at the very top of the page is the exact same phrase as the headline, making it distracting and unnecessary. The CTA button copy is as vague as it gets. “Submit” doesn’t say anything about the offer and likely doesn’t entice many visitors to convert. The CTA button color doesn’t stand out as much as it could, because green is used elsewhere on the page. Changing it to a more contrasting color like orange would likely draw more attention and result in more leads. The second CTA button at the bottom of the page should be removed. Since this is a completely different offer, it should have its own landing page. Adding trust signals and/or social proof (customer testimonials, company badges, etc.) would make prospects more comfortable and compelled to watch the webinar. In the decision stage The decision stage is what it all boils down to; where customers are made or prospects are lost. Up until this point of the buyer’s journey, your lead has been creating a list of potential brands to use as the solution to their problem - and now it’s time for them to make their decision based on what they’ve learned about you so far. During this make-or-break stage, advertising landing page offers include trials, demos, consultations, quotes, coupons, and vendor/product comparisons. Falcon Google isn’t the only advertising channel used to send prospects to landing pages. Here is a Sponsored Post on Facebook that Falcon uses to drive traffic to their landing page offering a demo: What the page does well: Cooperative CTA buttons all the way down the page give prospects ample chances to convert on the offer. When visitors click any of the buttons, they are brought to the bottom of the page to complete the form. Social proof throughout the page (company logos and customer testimonials) likely convinces others to request the demo, leading them to believe that if everyone else finds so much success with this company, then they will too. Bullet points and images to describe the main components of the software makes the page more engaging and easier for prospects to comprehend. What could be changed or A/B tested: The hyperlinked company logo may serve as a distraction, taking visitors off the page before getting the chance to convert. The CTA buttons don’t catch your eye or make visitors want to click. Most of them are the same color as their background, and even the blue ones don’t contrast as well as they could. “Free” demo is not mentioned until the very end of the page. Highlighting that the demo is free at the top will result in more customers because prospects will spend more time browsing the page and seeing the product benefits. The page is aesthetically pleasing. It appears professional and branded, it’s well-organized, includes sufficient white space, and follows the Z-Pattern layout all the way down. Missouri Table & Chair This is a Promoted Post on LinkedIn from Missouri Table & Chair: When prospects click on the Promoted Post, they are directed to this advertising landing page that the company uses in the decision stage of the buyer’s journey to encourage visitors to sign up for a free consultation: What the page does well: Trust seals directly beneath the form make it likely that prospects will feel comfortable converting on the offer. This is important since the company did not include a privacy policy link. The frame around the lead capture form helps to draw attention to it. The autofill function likely increases conversion rates, because it makes it easier and faster for prospects to complete the form. What could be changed or A/B tested: The company logo is hyperlinked, giving visitors an immediate way off the page before converting. Lack of copy likely leaves prospects wondering why they should convert on this offer. The CTA button copy is bland. Making it more benefit-centered and exciting, such as, “Schedule my free consult now!” would likely result in more customers. No privacy policy could deter prospects from giving their personal information because they don't know where it could end up. Source: