Build the most effective personalization strategy: A 4-step roadmap Along with “artificial intelligence”, “personalization” has been a hot topic among…Read blog postabout:Our top 7 blog posts of 2017
Continued here –
Build the most effective personalization strategy: A 4-step roadmap Along with “artificial intelligence”, “personalization” has been a hot topic among…Read blog postabout:Our top 7 blog posts of 2017
Continued here –
Reading Time: 7 minutes
Seriously. A quick google will show you that Unbounce, QuickSprout, Moz, Qualaroo, Hubspot, Wordstream, Optimizely, CrazyEgg, VWO (and countless others), have been writing tips and guides on how to optimize your landing pages for years.
Not to mention the several posts we have already published on the WiderFunnel blog since 2008.
And yet. This conversation is so not over.
Warning: If your landing page optimization goals are short-term, or completely focused on conversion rate lift, this post may be a waste of your time. If your goal is to continuously have the best-performing landing pages on the internet, keep reading.
Marketers are funnelling more and more money into paid advertising, especially as Google allocates more and more SERP space to ads.
In fact, as an industry, we are spending upwards of $92 billion annually on paid search advertising alone.
And it’s not just search advertising that is seeing an uptick in spend, but social media advertising too.
It makes sense that marketers are still obsessing over their landing page conversion rates: this traffic is costly and curated. These are visitors that you have sought out, that share characteristics with your target market. It is extremely important that these visitors convert!
But, there comes a time in every optimizer’s life, when they face the cruel reality of diminishing returns. You’ve tested your landing page hero image. You’ve tested your value proposition. You’ve tested your form placement. And now, you’ve hit a plateau.
So, what next? What’s beyond the tips and guides? What is beyond the optimization basics?
First things first: Let’s do a quick sanity check.
When you test your hero image, or your form placement, are you testing based on tips and recommended best practices? Or, are you testing based on a specific theory you have about your page visitors?
Tips and best practices are a fine place to start, but the insight behind why those tactics work (or don’t work) for your visitors is where you find longevity.
The best way to improve experiences for your visitors is to think from their perspective. And the best way to do that is to use frameworks, and framework thinking, to get robust insights about your customers.– Chris Goward, Founder & CEO, WiderFunnel
It’s very difficult to think from a different perspective. This is true in marketing as much as it is in life. And it’s why conversion optimization and A/B testing have become so vital: We no longer have to guess at what our visitors want, but can test instead!
That said, a test requires a hypothesis. And a legitimate hypothesis requires a legitimate attempt to understand your visitor’s unique perspective.
To respond to this need for understanding, WiderFunnel developed the LIFT Model® in 2008: our foundational framework for identifying potential barriers to conversion on a page from the perspective of the page visitor.
Get the LIFT Model poster, and challenge yourself to keep your visitor’s perspective in mind at all times. Use the six conversion factors to analyze your pages, and get optimization ideas!
The LIFT Model attempts to capture the idea of competing forces in communication, narrowing them down to the most salient aspects of communication that marketers should consider.
I wanted to apply the principles of Relevance, Clarity, Distraction, Urgency and Anxiety to what we were delivering to the industry and not just to our clients. And the LIFT Model is a part of that: making something as simple as possible but no simpler.– Chris Goward
When you look at your page through a lens like the LIFT Model, you are forced to question your assumptions about what your visitors want when they land on your page.
You may love an interactive element, but is it distracting your visitors? You may think that your copy creates urgency, but is it really creating anxiety?
If you are an experienced optimizer, you may have already incorporated a framework like the LIFT Model into your optimization program. But, after you have analyzed the same page multiple times, how do you continue to come up with new ideas?
Here are a few tips from the WiderFunnel Strategy team:
You should always err on the side of “This customer experience could be better.” After all, it’s a customer-centric world, and we’re just marketing in it.
“Landing page optimization”, like “conversion rate optimization”, is a limiting term. Yes, on-page optimization is key, but mature organizations view “landing page optimization” as the optimization of the entire experience, from first to last customer touchpoint.
Landing pages are only one element of a stellar, high-converting marketing campaign. And focusing all of your attention on optimizing only one element is just foolish.– Amanda Durepos, “Next level landing page optimization: Before and after the conversion”
From testing your featured ads, to tracking click-through rates of Thank You emails, to tracking returns and refunds, to tracking leads through the rest of the funnel, a better-performing landing page is about much more than on-page conversion rate lift.
One of our clients is a company that provides an online consumer information service—visitors type in a question and get an Expert answer. One of the first zones (areas on their website) that we focused on was a particular landing page funnel.
Visitors come from an ad, and land on page where they can ask their question. They then enter a 4-step funnel: Step 1: Ask the question > Step 2: Add more information > Step 3: Pick an Expert > Step 4: Get an answer (aka the checkout page)
Our primary goal was to increase transactions, meaning we had to move visitors all the way through the funnel. But we were also tracking refunds and chargebacks, as well as revenue per visitor.
More than pushing a visitor to ‘convert’, we wanted to make sure those visitors went on to be happy, satisfied customers.
In this experiment, we focused on the value proposition statements. The control landing page exclaimed, “A new question is answered every 9 seconds!“. Our Strategy team had determined (through user testing) that “speed of answers” was the 8th most valuable element of the service for customers, and that “peace of mind / reassurance” was the most important.
So, they tested two variations, featuring two different value proposition statements meant to create more peace of mind for visitors:
Both of these variations ultimately increased transactions, by 6% and 9.4% respectively. But! We also saw large decreases in refunds and chargebacks with both variations, and large increases in net revenue per visitor for both variations.
By following visitors past the actual conversion, we were able to confirm that these initial statements set an impactful tone: visitors were more satisfied with their purchases, and comfortable investing more in their expert responses.
As you think of landing page optimization as the optimization of a complete digital experience, you should also think of landing page optimization as part of your overall digital optimization strategy.
When you discover an insight about visitors to your product page, feed it into a test on your landing page. When you discover an insight about visitor behavior on your landing page, feed it into a test on your website.
It’s true that your landing pages most likely cater to specific visitor segments, who may behave totally differently than your organic visitors. But, it is also true that landing page wins may be overall wins.
Plus, landing page insights can be very valuable, because they are often new visitor insights. And now, a little more advice from Chris Goward, optimization guru:
“Your best opportunities for testing your value proposition are with first impression visitors. These are usually new visitors to your high traffic landing pages or your home page […]
By split testing your alternative value propositions with new visitors, you’ll reduce your exposure to existing customers or prospects who are already in the consideration phase. New prospects have a blank canvas for you to present your message variations and see what sticks.
Then, from the learning gained on landing pages, you can validate insights with other target audience groups and with your customers to leverage the learning company-wide.
Landing page testing can do more than just improve conversion rates on landing pages. When done strategically, it can deliver powerful, high-leverage marketing insights.”
Just because your landing pages are separate from your website, does not mean that your landing page optimization should be separate from your other optimization efforts. A landing page is just another zone, and you are free to (and should) use insights from one zone when testing on another zone.
A lot of marketers talk about landing page design: how to build the right landing page, where to position each element, what color scheme and imagery to use, etc.
But when you dig into the why behind your test results, it’s like breaking into a piñata of possibilities, or opening a box of idea confetti.
Why do your 16-25 year old, mobile users respond so favorably to a one-minute video testimonial from a past-purchaser? Do they respond better to this indicator of social proof than another?
Why do your visitors prefer one landing page under normal circumstances, and a different version when external factors change (like a holiday, or a crisis)? Can you leverage this insight throughout your website?
Why does one type of urgency phrasing work, while slightly different wording decreases conversions on your page? Are your visitors sensitive to overly salesy copy? Why or why not?
For many marketers, personalized landing pages are becoming more normal. And personalization opens the door to even more potential customer insights. Assuming you already have visitor segments, you should test the personalized experiences on your landing pages.
For example, imagine you have started using your visitors’ first names in the hero banner of your landing page. Have you validated that this personalized experience is more effective than another, like moving a social proof indicator above the fold? Both can be deemed personalization, but they tap into very different motivations.
From psychological principles, to validating your personalized experiences, the possibilities for testing on your landing pages are endless.
Your landing page(s) will never be “optimized”. That is the beauty and cruelty of optimization: we are always chasing unattainable perfection.
But your landing pages can definitely be better than they are now. Even if you have a high-converting page, even if your page is listed by Hubspot as one of the 16 best designed landing pages, even if you’ve followed all of the rules…your landing page can be better.
Because I’m not just talking about conversions, I’m talking about your entire customer experience. If you give them the opportunity, your new users will tell you what’s wrong with your page.
They’ll tell you where it is unclear and where it is distracting.
They’ll tell you what motivates them.
They’ll tell you how personal you should get.
They’ll tell you how to set expectations so that they can become satisfied customers or clients.
A well-designed landing page is just the beginning of landing page optimization.
The post How to get evergreen results from your landing page optimization appeared first on WiderFunnel Conversion Optimization.
As a valued customer, we’d like to…
For many eCommerce companies, the first personalization project begins with FNAME. We have become really good at personalizing emails because we know that it works. Emails personalized with recipients’ first names increase open rates by 2.6 percent.
Shoppers are more attracted to marketing that targets their interests and purchase patterns. This doesn’t only apply to emails–using personalization in your eCommerce branded store is the best way to build a relationship and keep customers converting.
The more often customers return, the better you become at delivering relevant suggestions and content for them. According to an Adobe study, 40% of online revenue comes from returning customers…who only represent 8% of site traffic. Using personalized recommendations, enterprises can build a stronger, more profitable relationship with their users.
Now is the time to optimize revenue opportunities and become better at selling to the right customers at the right time. Read on to learn how to use personalization to drive up average order value, or AOV.
Personalization doesn’t work if you don’t know anything about your customers. The more relevant and accurate data you gather, the more refined and detailed picture you can draw. Customers are happy to help you get to know them too. 75% of shoppers like it when brands personalize products and offers, while 74% of online customers get frustrated with a website when content that appears has nothing to do with their interests.
When customers sign up on your site or check out for the first time, use this opportunity to collect information. This will help you with informed promotion and planning recommendations in the future.
As your relationship grows, you can continue to learn more about your customers.
Finally, customers have the most information about themselves. Allowing them to personalize their own experience by sharing their gender or interest information is a simple way to ensure that you aren’t showing them irrelevant information or products.
Customer data can come from anywhere, and it’s necessary when personalizing experiences. In summary, look for the following data points:
Enabling social logins like Connect with Facebook will also help you get demographic information about your customers, without them having to provide it themselves.
Now that we’ve got a good picture of our customers, we can start personalizing their experience. There’re three main ways to do this—by segmenting, history, or trend analysis.
There are several ways you can personalize a customer’s experience even without asking for any information. When customers land on your site, you already know more about them than you might think.
Use geotargeting to show the correct language and currency.
Right now, I’m in Austria, so Wool and Gang default to Austria shipping rates and are showing me prices in Euros. This reduces concerns international customers might have about shipping abroad or currency exchange. Reducing concerns means an easier checkout experience, which means better conversions.
Using cookies to know if a customer is new or returning.
If they are new customers, prompt them with a pop-up module to sign up and get a discount on their first purchase. Welcome them to your site, explain who you are, and save their email addresses for future selling opportunities.
Spearmint LOVE offers 10% off for first-time visitors if they sign up for the newsletter. It’s a little bonus that later helps convert visitors at a higher value.
“Wholesalers” is another segment of customers who have different needs. Individual shoppers want quick, one-off purchases and may not be as likely to sign in or create accounts on branded sites.
But catering to wholesale clients by allowing them to sign in to receive special discounts and review orders without calling an account management team makes the experience much better for them. Clarion Safety sells industrial grade safety labels. This organization has created a special experience for wholesale customers that allows them to use different check-out options, such as “charge to account.”
Different paths signal different intents.
If they found your products through Pinterest, they are looking to browse and are more visual. If they clicked an email coupon, they could be price conscious and should be shown more sale items. Get inside your customers’ brains and show them what they want to see—this will provide you the highest chance of conversion.
After a relationship has been established between you and your customers—whether that’s just through visiting or years of purchasing history—you have information about them from their previous activity. Use this information to customize their experience, and upsell and cross-sell products that are relevant to them.
Before purchasing, visitors go back and forth with regard to an item when not sure. They might visit the same site multiple times in a week. A surefire way to get them to convert is to show them their recently viewed items whenever they visit your website. If you’re able to offer a discount on products that they’ve viewed multiple times, it might help you seal the deal.
EpicTV combines this strategy with a least purchase amount for free shipping. This means that visitors will usually add something from their recently viewed list just to achieve that perk.
When customers are viewing their carts, at that instance, you can use previous searches or purchases to suggest complementary items. Red’s Baby uses this method to suggest accessories for the main purchase and incrementally increase the AOV. I added a stroller to my shopping cart, and this site suggested matching accessories—all under $50. At this instance, suggesting other types of strollers wouldn’t be effective.
Think about what it’s like meeting customers in the real world. The more you see them, the more history you have of them. You might know that they have kids or that they like to play squash on weekends.
This context makes personalized recommendations and upsells easier. Try and replicate this online. Shopping at an eCommerce retailer doesn’t need to be impersonal, and it shouldn’t be.
Taking the time to build a better recommendation engine makes sense and helps generate additional revenue. According to Barilliance and data based on 1.5 billion online shopping sessions, personalized on-site product recommendations constitute 11.5% of revenue through eCommerce sites. That’s a big chunk of revenue to miss out on!
To optimize across all customer visits, dive into analytics and look for purchasing patterns. Do shoppers tend to return often if they buy a specific item? Do many shoppers buy a combination of items at the same time? Finding and taking advantage of these opportunities can help drive up AOV.
For example, recommending products that other customers bought helps crowd source the best options. Check out these suggestions by Blue Tomato when viewing an item.
Flash Tattoos speaks their customer’s language and makes their Recommendation section fun. “You’d also look good in” is a flattering way to suggest similar products across different styles.
If customers have viewed the shipping policy and not purchased, they might be hesitant about shipping costs. Try offering free shipping at a certain cart value to convert potentially cost-sensitive customers. Finding these patterns that expose reasons for cart abandonment helps create a better experience for your customers. They’ll feel like you are addressing their concerns before they even ask!
Now that you’re ready to start personalizing the shopping experience, we’ve got a few final tips for you:
When you’re suggesting or upselling, use your screen space wisely:
Remember the purpose of each screen, and don’t distract customers from completing their purchase. On the checkout screen, the single Call-to-Action should be to convert and pay for what they’ve selected. Cluttering the screen with additional products can reduce your overall conversion rate.
Personalization isn’t a set-it-and-forget-it tactic:
You need to constantly reevaluate your metrics, hypotheses, and experiments to keep getting better at selling to your customers. Don’t be afraid to try things out and get personal! Your customers will love it and reward you for it with higher AOVs.
The post Using Personalization To Increase AOV And Conversion Rates appeared first on VWO Blog.
Reading Time: 11 minutes
It’s Groundhog Day again.
Do you remember the Groundhog Day movie? You know… the one where Bill Murray’s character repeats the same day over and over again, every day. He had to break the pattern by convincing someone to fall in love with him, or something like that.
What an odd storyline.
Yet today, it’s reminding me of a pattern in marketing. Marketing topics seem to be pulled by an unstoppable force through fad cycles of hype, over-promise, disappointment, and decline – usually driven by some new technology.
I’ve watched so many fad buzzwords come and go, it’s dizzying. Remember Customer Relationship Marketing? Integrated Marketing? Mobile First? Omnichannel?
A few short years ago, everyone was talking about social media as the only topic that mattered. Multivariate testing was sexy for about five minutes.
Invariably, similar patterns of mistakes appear within each cycle.
Tool vendors proliferate on trade show floors, riding the wave and selling a tool that checks the box of the current fad. Marketers invest time, energy, and budget hoping for a magic bullet without a strategy.
Now, everyone is swooning for Personalization. And, so they should! It can deliver powerful results.
This post is over 3,000 words of personalization goodness. Get the full PDF now so that you can reference it later, and share it with your co-workers.
From simple message segmentation to programmatic ad buying and individual-level website customization, the combination of big data and technology is transforming the possibilities of personalization.
But the rise of personalization tools and popularity has meant the rise of marketers doing personalization the wrong way. I’ve lost track of the number of times we’ve seen:
That’s why, in collaboration with our partners at Optimizely, we have created a roadmap for creating the most effective personalization strategy:
Personalization and segmentation are often used interchangeably, and are arguably similar. Both use information gathered about the marketing prospect to customize their experience.
While segmentation attempts to bucket prospects into similar aggregate groups, personalization represents the ultimate goal of customizing the person’s experience to their individual needs and desires based on in-depth information and insights about them.
You can think of them as points along a spectrum of customized messaging.
You’ve got the old mass marketing approach on one end, and the hyper-personalized, 1:1, marketer-to-customer nirvana on the other end. Segmentation lies somewhere in the middle. We’ve been doing it for decades, but now we have the technology to go deeper, to be more granular.
Every marketer wants to provide the perfect message for each customer — that’s the ultimate goal of personalization.
Personalization solves the problem of Relevance (one of 6 conversion factors in the LIFT Model®). If you can increase the Relevance of your value proposition to your visitor, by speaking their language, matching their expectations, and addressing their unique fears, needs and desires, you will see an increase in conversions.
Let me show you an example.
Secret Escapes is a flash-sale luxury travel company. The company had high click-through rates on their search ads and directed all of this traffic to a single landing page.
The ad copy read:
Save up to 70% on Spa Breaks. Register for free with your email.”
But, the landing page didn’t reflect the ad copy. When visitors landed on the page, they saw this:
Not super relevant to visitors’ search intent, right? There’s no mention of the keyword “spa” or imagery of a spa experience. Fun fact: When we are searching for something, our brains rely less on detailed understanding of the content, and more on pattern matching, or a scent trail.
In an attempt to convert more paid traffic, Secret Escapes tested two variations, meant to match visitor intent with expectations.
By simply maintaining the scent trail, and including language around “spa breaks” in the signup form, Secret Escapes was able to increase sign-ups by 32%. They were able to make the landing page experience sticky for this target audience segment, by improving Relevance.
Pause. Before you dig any deeper into personalization, you should determine whether or not it is the right strategy for your company, right now.
Here are 3 questions that will help you determine your personalization maturity and eligibility.
Personalization is not a business practice for companies with no idea of how they want to segment, but for businesses that are ready to capitalize on their segments.– Hudson Arnold, Strategy Consultant, Optimizely
For companies getting started with personalization, we recommend that you at least have fundamental audience segments in place. These might be larger cohorts at first, focused on visitor location, visitor device use, single visitor behaviors, or visitors coming from an ad campaign.
If you haven’t categorized your most important visitor segments, you should focus your energies on segmentation first, before moving into personalization.
Personalization requires dedicated resources and effort to sustain all of your segments and personalized variations. To create a truly effective personalization strategy, you will need to proceduralize personalization as its own workstream and implement an ongoing process.
Which leads us to question three…
Personalization is a hypothesis until it is tested. Your assumptions about your best audience segments, and the best messaging for those segments, are assumptions until they have been validated.
Personalization requires the same inputs and workflow as testing; sound technical implementation, research-driven ideation, a clear methodology for translating concepts into test hypotheses, and tight technical execution. In this sense, personalization is really just an extension of A/B testing and normal optimization activities. What’s more, successful personalization campaigns are the result of testing and iteration.– Hudson Arnold
Great personalization strategy is about having a rigorous process that allows for 1) gathering insights about your customers, and then 2) validating those insights. You need a structured process to understand which insights are valid for your target audience and create growth for your business.
WiderFunnel’s Infinity Optimization Process™ represents these two mindsets. It is a proven process that has been refined over many years and thousands of tests. As you build your personalization strategy, you can adopt parts or all of this process.
There are two critical phases to an effective personalization strategy: Explore and Validate. Explore uses an expansive mindset to consider all of your data, and all of your potential personalization ideas. Validate is a structured process of A/B testing that uses a reductive mindset to refine and select only those ideas that produce value.
Without a process in place to prove your personalization hypotheses, you will end up wasting time and resources sending the wrong messages to the wrong audience segments.
Personalization without validation is simply guesswork.
If you have answered “Yes” to those three questions, you are ready to do personalization: You are confident in your audience segments, you have dedicated resources, perhaps you’re already doing basic personalization. Now, it’s time to build your personalization strategy by gathering insights from your data.
One of the questions we hear most often when it comes to personalization is, “How do I get ideas for customized messaging that will work?” This is the biggest area of ongoing work and your biggest opportunity for business improvement from personalization.
The quality of your insights about your customers directly impacts the quality of your personalization results.
Here are the 3 types of personalization insights to explore:
You can mix and match these types within your program. We have plenty of examples of how. Let’s look at a few now.
Are there general theories that apply to your particular business situation?
Psychological principles? UX principles? General patterns in your data? ‘Best’ practices?
Deductive personalization starts with your assumptions about how your customers will respond to certain messaging based on existing theories…but it doesn’t end there. With deductive research, you should always feed your ideas into experiments that either validate or disprove your personalization approach.
Let’s look at an example:
Heifer International is a charity organization that we have been working with to increase their donations and their average donation value per visitor.
In one experiment, we decided to test a psychological principle called the “rule of consistency”. This principle states that people want to be consistent in all areas of life; once someone takes an action, no matter how small, they strive to make future behavior match that past behavior.
We asked visitors to the Heifer website to identify themselves as a donor type when they land on the site, to trigger this need to remain consistent.
Notice there’s no option to select “I’m not a donor.” We were testing what would happen when people self-identified as donors.
The results were fascinating. This segmenting pop up increased donations by nearly 2%, increased the average donation value per visitor by 3%, and increased the revenue per visitor by more than 5%.
There’s more. In looking at the data, we saw that just 14% of visitors selected one of the donation identifications. But, that 14% was actually 68% of Heifer’s donors: The 14% who responded represent a huge percentage of Heifer’s most valuable audience.
Now, Heifer can change the experience for visitors who identify as a type of donor and use that as one piece of data to personalize their experience. Currently, we’re testing which messages will maximize donations even further within each segment.
Are there segments within your data and test results that you can analyze to gather personalization insights?
If you are already optimizing your site, you may have seen segments naturally emerge through A/B testing. A focused intention to find these insights is called inductive research.
Inductive personalization is driven by insights from your existing A/B test data. As you test, you discover insights that point you toward generalizable personalization hypotheses.
Here’s an example from one of WiderFunnel’s e-commerce clients that manufactures and sells weather technology products. This company’s original product page was very cluttered, and we decided to test it against a variation that emphasized visual clarity.
Surprisingly, the clear variation lost to the original, decreasing order completions by -6.8%. WiderFunnel Strategists were initially perplexed by the result, but they didn’t rest until they had uncovered a potential insight in the data.
They found that visitors to the original page saw more pages per session, while visitors to the variation spent a 7.4% higher average time on page. This could imply that shoppers on the original page were browsing more, while shoppers on our variation spent more time on fewer pages.
Research published by the NN Group describes teen-targeted websites, suggesting that younger users enjoy searching and are impatient, while older users enjoy searching but are also much more patient when browsing.
With this research in mind, the Strategists dug in further and found that the clear variation actually won for older users to this client’s site, increasing transactions by +24%. But it lost among younger users, decreasing transactions by -38%.
So, what’s the takeaway? For this client, there are potentially new ways of customizing the shopping experience for different age segments, such as:
This client can use these insights to inform their age-group segmentation efforts across their site.
(Also, this is a great example of why one of WiderFunnel’s five core values says “Grit – We don’t quit until we find an answer.”)
Ask your prospects to tell you about themselves. Then, test the best marketing approach for each segment.
Customer self-selected personalization is potentially the easiest strategy to conceptualize and implement. You are asking your users to self-identify, and segment themselves. This triggers specific messaging based on how they self-identified. And then you can test the best approach for each of those segments.
Here’s an example to help you visualize what I mean.
One of our clients is a Fortune 500 healthcare company — they use self-selected personalization to drive more relevant content and offers, in order to grow their community of subscribers.
This client had created segments that were focused on a particular health situation, that people could click on:
These segments came from personas that this client had developed about their subscriber base.
Once a user self-identified, the offers and messaging that were featured on the page were adjusted accordingly. But, we wouldn’t want to assume the personalized messages were the best for each segment. You should test that!
In self-selected personalization, there are two major areas you should test. You want to find out:
For this healthcare company, we didn’t simply assume that those 5 segments were the best segments, or that the messages and offers triggered were the best messages and offers. Instead, we tested both.
A series of A/B tests within their segmentation and personalization efforts resulted in a doubling of this company’s conversion rate.
Developing a personalization strategy requires an audience-centric approach. The companies that are succeeding at personalization are not picking segments ad hoc from Google Analytics or any given study, but are looking to their business fundamentals.
Once you believe you have identified the most important segments for your business, then you can begin to layer on more tactical segments. These might be qualified ‘personas’ that inform your content strategy, UX design, or analytical segments.
If this whole thing is starting to feel a little complex, don’t worry. It is complex, but that’s why we prioritize. Even with a high-functioning team and an advanced tool, it is impossible to personalize for all of your audience segments simultaneously. So, where do you start?
Optimizely uses a simple axis to conceptualize how to prioritize personalization hypotheses. You can use it to determine the quantity and the quality of the audiences you would like to target.
The x-axis refers to the size of your audience segment, while the y-axis refers to an obvious need to personalize to a group vs. the need for creative personalization.
For instance, the blue bubble in the upper left quadrant of the chart represents a company’s past purchasers. Many clients want to start personalizing here, saying, “We want to talk to people who have spent $500 on leather jackets in the last three months. We know exactly what we wanna show to them.”
But, while you might have a solid merchandising strategy or offer for that specific group, it represents a really, really, really small audience.
That is not to say you shouldn’t target this group, because there is an obvious need. But it needs to be weighed against how large that group is. Because you should be treating personalization like an experiment, you need to be sensitive to statistical significance.
The net impact of any personalization effort you use will only be as significant as the size of the segment, right? If you improve the conversion rate 1000% for 10 people, that is going to have a relatively small impact on your business.
Now, move right on the x-axis; here, you are working with larger segments. Even if the personalized messaging is less obvious (and might require more experimentation), your efforts may be more impactful.
Food for thought: Most companies we speak to don’t have a coherent geographical personalization strategy, but it’s a large way of grouping people and, therefore, may be worth exploring!
You may be more familiar with WiderFunnel’s PIE framework, which we use to prioritize our ideas.
How does Optimizely’s axis relate? It is a simplified way to think about personalization ideas to help you ideate quickly. Its two inputs, “Obvious Need” and “Audience Size” are essentially two inputs we would use to calculate a thorough PIE ranking of ideas.
The “Obvious Need” axis would influence the “Potential” ranking, and “Audience Size” would influence “Importance”. It may be helpful to consider the third PIE factor, “Ease”, if some segmentation data is more difficult to track or otherwise acquire, or if the maintenance cost of ongoing messaging is high.
To create the most effective personalization strategy for your business, you must remember what you already know. For some reason, when companies start personalization, the lessons they have learned about testing all of their assumptions are sometimes forgotten.
You probably have some great personalization ideas, but it is going to take iteration and experimentation to get them right.
A final note on personalization: Always think of it in the context of the bigger picture of marketing optimization.
Insights gained from A/B testing inform future audience segments and personalized messaging, while insights derived from personalization experimentation informs future A/B testing hypotheses. And on and on.
Don’t assume that insights gained during personalization testing are only valid for those segments. These wins may be overall wins.
The best practice when it comes to personalization is to take the insights you validate within your tests and use them to inform your hypotheses in your general optimization strategy.
** Note: This post was originally published on May 3, 2016 as “How to succeed at segmentation and personalization” but has been wholly updated to reflect new personalization frameworks, case studies, and insights from Optimizely. **
Still have questions about personalization? Ask ’em in the comments, or contact us to find out how WiderFunnel can help you create a personalization strategy that will work for your company.
The post Build the most effective personalization strategy: A 4-step roadmap appeared first on WiderFunnel Conversion Optimization.
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We have hardly seen through the first month of the year and the internet is already overwhelmed with the advice and trend pieces on eCommerce.
In this post, however, we specifically focus on those trends that can influence eCommerce conversion rates this year. It is important to keep a watch on such trends to keep ahead of the game.
Let’s read through what eCommerce experts are saying.
Effective site search is well known for increasing website conversion rates. Weblink’s internal study for 2016 points out that shoppers who use internal site search converted at a 216% higher rate than those who do not.
In 2014, Smashing Magazine benchmarked the search experience of the 50 top-grossing US e-commerce websites, revealing a lot of untapped potential:
According to Paul Rogers, 2017 will see more and more eCommerce businesses fix and optimize their on-site search in order to increase their conversion rates.
Paul Rogers, eCommerce consultant
I think an area of eCommerce that more and more merchants are starting to address, with a view to optimizing conversion metrics, is on-site search. Many of the clients I work with have upped their game in this area this year, making use of things like self-learning capabilities (via a third-party solution, supporting merchandising), natural language processing (to better understand more complex queries), product / category / attribute boosting and also promoting the use of the function.
In my experience, users who complete a search are considerably more likely to convert. I’ve seen positive results from making search boxes more prominent and more of a core navigation focus (through encouraging more complex queries like ‘search for product, SKU, brand or help’ for example). There are some really good, advanced solutions available for eCommerce stores now that can handle far more complex queries and drive more trade — I really like Klevu for the NLP and catalog enrichment side of things, but Algolia is very strong too.
Using a third-party solution is generally the best route for optimizing search, as the majority of the eCommerce platforms on the market (with the exception of enterprise systems like Oracle Commerce Cloud and IBM Websphere) have weak search technology, some of which are unable to process even the most simple queries.
A survey conducted by BloomReach 2015 revealed that approximately half of the online consumers conduct their first product search on Amazon. The survey gives some interesting insights into how and why Amazon continues to dominate American e-commerce market year-on-year.
In fact, the percentage of people who search for a product first on Amazon has gone up from 30% in 2012 to 44% in 2015. Check the graph for numbers on first searches made on Amazon vs. search engines vs. retailer websites.
Andrew Youderian believes that the same trend will continue well into 2017 unless other players are able to build a brand connection with customers.
Andrew Youderian, eCommerce entrepreneur
I think many merchants in 2017—especially those in the U.S.—will see continued downward pressure on their website conversion rates due to Amazon. As Amazon continues to gobble up market share, they are increasingly becoming the go-to place for consumers looking to purchase online. Unless merchants are selling something unique or have a strong brand connection with their customers, it will be difficult to win this battle, and it’s a transition that many merchants haven’t yet made.
The main trend for 2017 is the widespread maturing of the Conversion Rate Optimization industry. It is reminiscent of the usability and analytics industry a decade or so ago. Budgets are on the rise, companies are adopting a structured approach to optimization, and hiring in-house staff for the same.
Chris backs his statement with an interesting study by eConsultancy, according to which over half of companies plan to increase their conversion optimization budgets in 2017. The whole CRO industry will attract attention from the C-suite, he adds further.
A survey conducted by eConsultancy in 2013 concluded that 94% of the in-house marketers consider website personalization to be critical to the success of the business. This popularity of personalization in eCommerce has grown over the years. Evergage combines extensive data on personalization in a stats roundup for 2016. The gist of the report is that consumers are likely to buy from a retailer that:
While a lot is being discussed on personalization since long, Tracey Wallace opines that 2017 is going to be the year of personalization.
Tracey Wallace, Editor in Chief at Bigcommerce
The eCommerce industry has been talking about personalization for a while, without much data or fruition. In 2017, I think personalization is going to be the key to more sales from your already existing customers –– i.e. driving up AOV and retention. With so many channels for customers to check out on (and most brands being at least multi if not omnichannel), what will make them checkout on *your* webstore? VIP programs, special discounts, and early access will help to foster loyalty and drive up repeat sales. Plus, you can use this same type of segmentation to sell B2B and wholesale without having to take every single call. 2017 will be about efficiency, and there’s nothing more efficient than getting people who have already purchased from you to buy again, and again, and again.
Throughout the day, the one device that consumes most of our time is mobile. comScore reports that digital media time in the U.S. has exploded recently – growing nearly 50 percent in the past two years, with more than three-fourths of that growth directly attributable to the mobile app.
Since mobile plays a critical role in significantly increasing reach, awareness, and engagement, it is time that eCommerce players start giving it the due attention. Look at the following graph to see how mobile and tablet usage has been increasing over time.
Google has already shown its inclination towards mobile by announcing a “mobile-first” culture. As a result, Accelerated Mobile Pages (AMP) is being talked about a lot.
William Harris, Growth Marketer & Entrepreneur
One of the biggest trends in 2017 will be the growth of AMP. I tested this out with a few merchants on Shopify Plus when they were running the beta, and the results were impressive.
We know that stripping pages down to the necessary elements tends to increase conversion rates. We know that faster load times tend to increase conversion rates. So when you combine the both, it only makes sense that conversion rates will go up on mobile devices. Since mobile accounts for the majority of website traffic, that’s where the biggest increase in conversions will come in 2017.
Look to see more merchants adopting AMP and pushing the mobile conversion rate even higher (especially when AMP gets better and more flexible).”
The busy consumer is looking for smarter ways to shop. While he browses his mobile to make a mental to-buy list, he compares the best deals on a desktop for making an informed purchase.
For retailers, there lies an opportunity in this challenge. With the help of buy buttons, social commerce has enabled eCommerce players convert the buyer at the first point of contact – mobile, tablet, desktop, email, Facebook, Pinterest, or anywhere else.
Nicole Leinbach Reyhle, founder, Retail Minded Magazine
The buyer journey will always evolve and as a result, retailers must, as well. Among the ways I believe eCommerce, in particular, will see change in the year ahead is by the introduction of smart buy buttons. Such buy buttons do not need as many steps to purchase as they have in the past. This will undoubtedly help conversion rates, as well as connect consumers to brands more efficiently and more quickly than ever before. Through the introduction of buy buttons via social media, email, video platforms and other digital avenues, I believe that customers will be able to skip steps they have not been able to in the past. And, as a result, retailers will benefit with stronger sales and customer engagement.
Personalization, on-site optimization, the continuous rise of Amazon, conversion rate optimization, buy buttons—eCommerce businesses can use these trends to their advantage in 2017.
Have any of the trends listed above had any impact on your business? Tell us and our readers in the comments section below.
The post 2017 eCommerce Conversion Rate Trends That Are Here to Stay appeared first on VWO Blog.
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Consumers in the digital age want an integrated shopping experience. They might browse an eCommerce website on mobile but ultimately make a purchase from desktop. Or they might pay online, but pick up the purchased item from the store.
Such user behavior has been highlighted by a 2014 GfK study: “With people constantly moving between devices, it is important for marketers to reach their audience across all platforms. Brand experiences should be consistent, allowing for people to begin an activity on one device and finish on another.”
In this post, we discuss a robust omnichannel strategy that can help eCommerce enterprises create such integrated experiences across devices. The strategy includes:
But before we begin, let’s see how an ideal omnichannel experience for a consumer, say “Sarah” would look like:
Sarah is checking Instagram from her mobile and likes a dress her friend is flaunting. She visits the retailer’s website on mobile. She adds the product to her “wishlist” on mobile. Later during the day, she accesses her wishlist on the desktop, with the decision to make a buy. She chooses the option “inform when available in my size” and 3 days later, gets an email notifying her about the availability of the dress. It also informs her that “click and collect” is available on the product. She decides to pick up the dress from a physical store.
So how do eCommerce enterprises go omnichannel successfully? Let’s talk about the three steps.
The fact that people toggle among multiple devices throughout the day makes understanding the cross-device user behavior an absolute essential for eCommerce enterprises. Traditional analytics tracking tools such as Google Analytics do not offer the scope for establishing a connect between users and their disparate gadgets. Cross-device tracking removes this barrier for eCommerce enterprises and enables them to understand their users’ behavior across all touchpoints.
Cross-device tracking allows enterprises to understand whether a person browsing a website from smartphone X is the same person who made the purchase from laptop Z. Such information is important to rectify conversion credit allocated disproportionately to the last device of purchase. So if the use of mobile devices leads to desktop purchases, eCommerce enterprises might want to spend more on mobile ads and mobile website optimization.
There are two main methods to track cross-device user behavior—deterministic and probabilistic.
This methodology makes use of user’s signin information. As users are required to sign in to the website on each device they use, enterprises can track their behavior across all touchpoints. User Authentication is a type of deterministic device matching. It uses specific identifiers such as a customer ID, signin information, and so on to study and form a link between user behavior across devices.
Unlike deterministic device matching, this cross-device tracking technique does not rely solely on the user’s signin information. As the name indicates, this method computes the probability that various devices belong to or have been used by the same individual. An example of how probabilistic device matching works is extrapolation. For example, if a mobile and a tablet use the same Internet connection, it can be extrapolated that they belong to the same household. Device Fingerprinting is another famous probabilistic cross-device tracking technique. It combines device settings and browser options with some other attributes such as WiFi info, IP address, and more to identify users.
The next step, after tracking and understanding user behavior across devices, is to create seamless experiences for your users.
Walmart CEO, Doug McMillon shares his thoughts on a seamless customer experience:
“Ultimately, customers don’t care about what channel they’re shopping in or about how we deliver them a product or service. They simply know they’re shopping with Walmart.”
For Walmart, no matter what channel their customers buy from, it is important that they recognize the brand and get the same shopping experience throughout. Creating cohesive, consistent brand voice/experience can help eCommerce enterprises pave trust and encourage strong engagement, and, therefore, improve sales.
Other than brand consistency, a smooth and seamless shopping experience also constitutes customer experience. Hubspot talks about Oasis, a UK fashion retailer, in their seven inspiring examples of omnichannel user experience. On entering one of their stores, you’ll find sales associates walk you through all the product-related information using iPads. So, just in case something is out of stock, the staff places an online order for the customer and the item is shipped directly to customer’s home.
Here’s how Oasis uses iPads in-store to assist customers:
eCommerce enterprises should focus on the following points for providing a superior omnichannel shopping experience:
A post on Think with Google reports that 75 percent of the shoppers who find local retail info in search results helpful are more likely to visit stores. For eCommerce enterprises, this data opens up a number of opportunities. For example, eCommerce enterprises can inform online customers looking for a particular item online about it’s availability at a nearby store. To make this activity more effective, they can use geo-targeting to drive more in-store purchases from people from the local vicinity who have an intent to buy. Moreover they can also provide information such as local store hours, directions to the local store, or any discounts running in the store. Providing local relevant information online can also help convert more of those shoppers who view shopping as an experience and not just a purchase activity. Retailers, on the other hand, can benefit from the impulse buying tendency of people who exhibit a search online, shop local behavior.
A Search Engine Journal post lists 10 popular online payment solutions such as Amazon Payments and Google Wallet. As these options are trustworthy and secure, these will encourage users to pay from any channel that they use.
Deploying these payment solutions is a win-win for both the parties, because these solutions are convenient, quick, and trustworthy.
The interconnected and digitally empowered consumer demands relevant and personalized experience. For an omnichannel player, this would mean understanding which devices are used by the consumers and how. For example, Evergage talks about how eBay creates omnichannel personalization for its users. The eBay mobile app allows users to enable push notifications, which informs them about the start or end of any auction. The desktop site, on the other hand, is designed for easy search and window shopping.
Innovation and technology enhance the omnichannel experience both for buyers and eCommerce enterprises. Using virtual reality, for example, can help eCommerce players make use of virtual environments that are otherwise difficult to create inside a store. For the user, these technologies can address buyer’s uncertainty.
For example, before making a decision to buy a hat, a person would like to know which hat type, color, width, and so on would suit him the best. Without physically trying a number of different hats, he can use such technologies to find out what looks best on him. For the eCommerce enterprise, this means being able to provide their users with better services and experience even if all the types of hats are not physically in store.
Tommy Hilfiger also provides a fantastic in-store VR experience. As a result, shoppers can view virtual catwalks and shop the season’s runway styles.If you are looking for more on the who and how of virtual and augmented reality in retail and eCommerce, here’s a Forbes post to read.
The following image shows customers experiencing Tommy Hilfiger VR:
Customer experience might suffer if an eCommerce enterprise is not structured to meet the requirements of omnichannel retail. When departments operate in silos, the problem of sales attribution often arises. Such conflicts are unhealthy, as they can jeopardize the enterprise’s ability to deliver a smooth omnichannel experience.
An organizational structure that is better aligned for omnichannel, requires various departments within an organization to work together and be accountable to each other. Macy’s, for example, has also completely restructured their merchandising and marketing functions. They have also created chief omnichannel officer positions in their organization.
“Here is the approach I suggest:
Ultimately, KPIs and incentives need to balance near-term and long-term goals such as maximizing profitability in the short-term versus growing market share. Also, enterprise success must always be prioritized over success in an isolated channel.”
While creating customer-centric experiences is the key to succeeding with omnichannel, it begins with understanding user behavior and extends to framing the right kind of organizational structures. There is a huge scope for eCommerce enterprises to adopt and excel at an omnichannel level, given that they make use of user information, technology, customer service, and their internal structures efficiently.
Have feedback on how eCommerce enterprises can develop a robust omnichannel strategy? Please leave a comment.
The post Going Omnichannel | A Robust Framework for eCommerce Enterprises appeared first on VWO Blog.
Hi [FIRSTNAME], Thanks for ordering your free copy of the [LEADMAGNET] eBook, we really hope the tips provided help [ORGANIZATION] grow its customer base and take its revenue to the next level. Before you go [FIRSTNAME], I’d love to know what specific problems both you and [ORGANIZATION] are facing so I can better tailor future materials to your needs. You’ve seen the likes of the above before. It’s one of the many cookie cutter email openings you’re probably sick of receiving. Sure, it adheres to the basic rules of personalization. It mentions both the user’s name, organization and even goes…
The post Is 1:1 Marketing Personalization a Realistic Possibility? appeared first on The Daily Egg.
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Once upon a time, in the not-so-distant past, people considered websites to be a prime indication of how users’ attention was brief and unforgiving. Remember the dreaded bounce rate?
Remember the numerous times you worried that your content and graphics might not be 100% clear to users? That was nothing. Compared to mobile, engaging users on the web is a piece of cake.
The post Driving App Engagement With Personalization Techniques appeared first on Smashing Magazine.
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While eCommerce enterprises realize the impact of customer retention on revenue, there are a number of key challenges that keep them from holistically implementing customer retention strategies.
One such challenge is the data complexity involved with calculating certain key metrics such as retention rate. As a result, businesses are making decisions per the metrics that might not be critical to long-term success. 2016 Retention Marketing report provides statistical evidence to why eCommerce organizations need clarity in their retention rate metrics.
Declining customer loyalty is affecting customer retention in a big way too. A (2015) research conducted by Accenture reports, “Just over one-quarter of U.S. consumers (28 percent) feel very loyal toward their providers and only about one in three (31 percent) are willing to recommend them to others.”
Competition demands eCommerce establishments to outgrow mediocrity and scale from average to elite. In this blog post, we highlight how optimizing their customer retention strategy (infused with actionable tips) can help eCommerce enterprises do exactly that!
To allocate marketing budget sensibly, eCommerce establishments need to understand where and what they are putting money and efforts into. Even before investing in a customer retention strategy, enterprises must focus on identifying their high-value customers. Centering retention efforts around high-value customers, as opposed to average customers, can yield considerably higher value in terms of RoI.
Digging into metrics such as customer lifetime value, average order value, purchase frequency, price sensitivity, and so on helps identify high-value customers. This post by eConsultancy talks about how you can do that.
Tracking and analyzing on-site behavior of high-value customers is also critical to optimizing the customer retention process. Tools like heatmap and visitor recordings can help understand collective and individual on-site user behavior respectively.
It is also important to understand the implication and usage of ‘churn rate’ correctly for your high-value customers. Instead of viewing it as a transactional metric, eCommerce enterprises should consider it to be a behavioral indicator. Harvard Business Review points out talks that enterprises are fixated with churn as a number instead of looking at it as a measure for improvement. The article also details on other mistakes that businesses make in using churn rate.
Actionable Tip: Use Net Promoter Score surveys to find out who your promoters, passives, and detractors are. Think of promoters as people who can drive more conversion and positive influence for your business. In this way, they are your high-value customers. Focusing efforts around retaining them is likely to lift your business value.
Feedback helps fill the gap between what businesses offer and what their users actually want, in terms of products, services, and/or experiences. MarketingSherpa Ecommerce Benchmark Study 2014 establishes that companies who make changes to their website per customer feedback had a success score of almost 8/10.
Displaying encouraging reviews on the website, for example, can help eCommerce establishments increase not just conversions but also credibility—something that is extremely important for retaining customers long term. The Deloitte Consumer Review Consumer Review Report 2014 provides some interesting statistics in a graph that we have borrowed for the purpose of this post.
Testimonials and surveys are the two other indispensable feedback mechanisms. Surveying your repeat visitors on their satisfaction with your product/services, suggestions for improving service quality, and so on can help you identify areas of improvement for your business.
On the other hand, on-page surveys (OPS)/voice-of-customer surveys trigger questions real-time and typically aim at addressing pain points on websites. Nevertheless, choosing the right trigger for your OPS is critical to soliciting feedback. Some common examples of OPS triggers are listed below:
Qualitative feedback obtained by OPS can also be of great value for optimizing purchase experiences, which can eventually increase retention. Here’s a VWO post – 10 tips on optimizing website surveys for soliciting better response.
Actionable Tip: Negative reviews don’t hit a business as hard as not responding to them can. Moreover, customers value businesses that are quick in accepting and amending their mistakes. While not all negative feedback is authentic, genuine resentments provide valuable insights into the business or product aspects lacking in your business. Check out this article for a complete approach on tackling negative reviews/feedback—right from digging into the problem to solving the problem to requesting customers for updating their review.
Data about user behavior/activity as well as feedback lays the foundation for businesses to continuously improve user experience. However, it’s easier said than done. eCommerce enterprises not only need to continuously upgrade their technology, but also must provide consistent experiences to users across devices.
According to Mckinsey customer-experience survey 2014, “measuring satisfaction on customer journeys is 30 percent more predictive of overall customer satisfaction than measuring happiness for each individual interaction, establishing that consistency on the most common customer journeys is an important predictor of overall customer experience and loyalty.”
A customer journey can be considered as the sum of all experiences that customers go through while interacting with a website. It is an aggregate measure – good and bad – across different touchpoints.
That said, customer ‘satisfaction’ is not enough. Enterprises, in a digital world that is rapidly transforming, need to focus on customer delight and this requires them to be not just customer-centric but customer-obsessed. The Warehouse does this exceptionally well. By focusing on what really works for their customers, it has been able to increase their online sales from $18.8 million in 2011 to $149.2 million in 2015.
Most importantly, creating an exceptional user experience cannot be possible without personalization. eCommerce enterprises who want to move from being average to elite should focus on providing personalized services across human and digital touch points. The power of personalization can also be harnessed to form an emotional connect with customers, ultimately driving retention and long-term customer relationships.This would require identifying emotional motivators that customers associate with and then crafting personalized messages around those motivators.
Consider ‘convenience’ to be an emotional motivator. eCommerce enterprises can use personalized messages on their website focused around this emotion that propels people to buy. Warby Parker does exactly this by offering it’s customers a chance to try what they like before they buy.
Actionable Tip: eCommerce establishments must focus on the 3 Es of experience – ease, efficiency, and emotion, as identified by Forrester Research. Storytelling is an effective tactic that can be used for establishing emotional connect with customers. Consider Everlane. The brand takes the story telling approach to communicate who and what they are, and what they do. They are able to establish trust and transparency – two values with which they establish an emotional connect with their customers.
Creating relevant post-sale messaging requires eCommerce enterprises to understand customer purchase history and behavior. It would be too soon to send out ‘We miss you here at…’ to someone who made his/her last purchase from you only a week back. What would be relevant instead is a cross-sell.
Here’s an example: A customer bought a boho necklace from your website. Now within a week of purchase, you could send an email to her/him, advertising the earrings available on your website that she could easily and perfectly pair with the necklace.
Moreover, not everyone who revisits or re-engages with your eCommerce website would have an intent to make a new purchase. You can give those sales emails a break. Let the goal be engagement.
This eMail from Boden is an excellent example on how to keep customers engaged even after a purchase.
Your post-sale messaging strategy can include sending out newsletters, articles, and product usage tips.
Sold a peppy scarf recently? Your THANK YOU email can contain a video on 20 trendy ways to wrap a scarf in less than 5 minutes.
Actionable Tip: Another way of retaining your customers through post-sale messages is to keep sending them replenishment reminders (in case your store sells replenishable items). This would require you to keep track of the standard purchase cycle for the product and the customer’s average frequency of the product or order. Read some interesting examples of replenishment emails on this article on Ometria.
eCommerce enterprises must steer their efforts towards retaining those customers who can create more value for the business. An effective and optimized customer retention strategy that comprises understanding and analyzing user behavior, soliciting feedback, improving customer experience, and crafting relevant messaging, can help businesses retain such customers.
What are you doing to retain your valuable customers? Drop us your suggestions or tips in the comments section below.
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For interaction designers, it’s becoming common to encounter privacy concerns as part of the design process. Rich online experiences often require the personalization of services, involving the use of people’s information.
Because gathering information to personalize a customer experience can interfere with the overall experience — with negative consequences for the business — how do we navigate this increasingly difficult territory? What are the guidelines to follow when using data to personalize digital experiences, and how can organizations help people feel comfortable with personalization services that research clearly shows people want?