AI+Human is magic: 3 Lessons from the Stitch Fix IPO About Personalization

Do you remember when was the last time you had fun shopping for new clothes? Me neither.

Over the past several years, the cycle of searching for, trying on, buying, and returning clothes has lost whatever joy it used to bring. In retail shops, you spend more time trying to find parking or standing in the checkout lines, than actually looking for what you like. Online, the sheer amount of selection is dizzying; you’re caught in a maze of price comparisons and unreliable customer reviews. And when you finally make a purchase, it’s inevitably the wrong size, triggering an arduous return process.

So, when I started using Stitch Fix recently, it was like stumbling upon an oasis of personalization, usability, and — yes! — fun in the otherwise lifeless fashion-buying desert. If you have read some of my earlier posts, you know by now that I am a fan. And I’m not alone. Founded by entrepreneur Katrina Lake in 2011, Stitch Fix filed for its IPO last Thursday. According to its filing, the startup has grown to serve more than 2 million customers, the vast majority of which are repeat buyers. In fiscal 2017, Stitch Fix reached nearly $1 billion in sales.

With so many other clothing retailers struggling, and in the face of intense competition from giants like Amazon, how is Stitch Fix succeeding?

In a word: personalization. On the road to its IPO, Stitch Fix has demonstrated three crucial lessons about the power of 1:1 marketing, made scalable by technology.

1. Every Customer Is Different; Every Experience Should Be Different

Here’s how StitchFix works:

You fill out a fashion profile on their website and pay a $20 styling fee. Using its proprietary data science/AI fashion-matching technology, plus the expertise of a personal stylist, Stitch Fix selects a mix of five clothing items and accessories and ships them to you. You can try on the clothes, purchase what you want, and send back the rest. Shipping is free both ways. Customers like me appreciate Stitch Fix for its seamless buying experience. But we love it for its personalization.

  • No two shipments are the same. Each is tailored to the fashion taste of an individual customer, yet dialed into modern trends.
  • As you continue to use Stitch Fix, it “learns” more about you. The fashion matching technology hits home more often than not, and your returns become less frequent.
2. Data Can Make Your Customers Feel Human

One of the worst aspects of digitization is being treated as faceless. The genius of Stitch Fix is that it uses numbers to re-humanize people. Their personalization technology starts by gathering 85 data points on each of its customers. The Stitch Fix IPO filing proclaims: “Our data science capabilities fuel our business.” Stitch Fix Chief Analytics Officer Eric Colson heads up the algorithm team that matches customers to clothing. He previously did a similar job at Netflix, another company that struck gold after realizing its role wasn’t to push products, but to engage with customers on an individual level — and smart use of data science is the way to scale the whole thing.

3. AI + Humans = Magic

The proprietary Stitch Fix algorithms are powerful tools. And they work best in the hands of experts who know how to deploy them to solve real-world fashion dilemmas. When I ordered from Stitch Fix, a computer program may have done the heavy analytics, but one of the company’s 600 stylists applied the finishing touches. As YEC points out, “In this way, the recommendation technology enables humans to do their jobs better, not the other way around.”

The Stitch Fix IPO emerged from the realization that personalization for each and every customer can be scalable — thanks to data science, algorithms, and artificial intelligence.

Using Real-Time Customer Data for 1:1 Marketing

With the right technology, you can apply the same approach to your marketing. Whether you’re reaching out through email, push notifications, SMS, or any other channel, you can tailor your message to each customer, drawing on real-time data for 1:1 marketing.

To learn more, download “The Path to Predictive 1-to-1 Marketing”.

3 Re-engagement Campaigns You Can Run In FB That Will Grow Your Revenues

With more than 2B monthly active users in Facebook, Facebook is a great channel for customer acquisition. But with the power of your first party customer behavior data, you have a big opportunity to run re-engagement campaigns using Facebook Custom Audiences that drive your revenues.

You have access to powerful first party data around user engagement, browsing and purchase behavior that you can add on top of Facebook user data such as user age, gender and interests. Create segments based on real time customer behavior such as ‘opened email’, ‘clicked on sms message’ etc. and automatically sync them with Facebook, so you can run high performing and targeted re-engagement campaigns.

Convert users that opened emails

Customers who opened emails are more likely to convert after seeing an ad. Real-time audience sync based on your first party behavioral data helps you maximize conversion by sending targeted re-engagement campaigns to these users on Facebook.

Bring back users that are inactive or at risk of churn

On average people spend more than 20 minutes a day on Facebook and for those in US that is up to 40 minutes a day. That screams opportunity. Reach out to users where they spend time. Target inactive users where they are most actively engaged and bring them back with reactivation campaigns.

Nurture users with automated campaigns across their life-cycle

Users interact across different channels. By adding Facebook as a re-engagement channel, you can create seamless cross channel experiences that nurture your users. Automate life-cycle specific campaigns based on where users are on their customer journey such as,

  • Welcome campaigns to new users
  • Re-sell/re-engage campaigns to one-time customers
  • Loyalty campaigns to repeat customers

In essence, by importing and syncing your behavior data with Facebook custom audiences in real-time, you can re-target users based on their upto-the-moment behavior. Automate campaigns based on real time behavior for the best engagement.

To learn how you can improve the ROI of your Facebook retargeting campaigns, see “Big target is the wrong target: Improve the effectiveness of Facebook retargeting“.


Interested in learning more? Check this out for more information how Blueshift can automatically sync your segments with Facebook in realtime.


A Big Target is the Wrong Target: How to Increase Effectiveness of Facebook Retargeting

Targeting everybody is targeting nobody. 

With average CPC rates ranging from $2 up to $5, broad targeting on Facebook can soon get expensive and highly ineffective. But by bringing your first party customer and behavioral data to Facebook, you can create precise audience segments that improve the ROI of your ad spend.

Create segments based on user behavior and sync with Facebook

Segment users based on a unified view of their cross channel behavior in real time (opened email, clicked on SMS message etc) and sync these segments in real-time with Facebook Custom Audiences to drive high performing campaigns.

Send the right campaign to the right audience

Targeting is not effective without relevant campaign messaging. Tailor segment specific campaigns such as send welcome campaigns to new users, re-engagement campaigns to inactive users and loyalty messages to regular users for lift in engagement.

With automated audience sync in “real-time” and precise retargeting, you can be sure your ad dollars pay off.

Are you using Facebook for re-engaging your users? See “3 re-engagement campaigns you can run in FB that will grow your revenues“.

 


Learn more on how Blueshift can automatically sync your segments with Facebook in realtime.


 

Blueshift partners with branch to offere personalized deep linking for email, mobile

Branch and Blueshift: Enabling seamless cross-channel personalization

With Blueshift’s personalization and Branch’s deep linking capabilities, marketers can now deliver  frictionless personalized experiences to their users across all channels.

Let’s take the instance of Jane. Jane is browsing through email on her mobile phone during her short break, and an email promotion for a weekend get-away grabs her attention. Clicking on the email leads her to the app’s home page where she spends a few secs looking for the promotional offer. Frustrated, she moves on to the next email assuming the get away is not meant to be, and makes alternate plans for the weekend. Not only did Jane not convert, she also had a frustrating experience with the app, making it less likely for her to go back.

In the example above, if Jane did not have the app installed, she might have been taken to the right page on the mobile website in her browser, albeit without any of the advantages of frictionless transaction on the app. Just like mobile websites have URLs that can “deep-link” to the right content, marketers need the ability to deep-link into mobile apps. Additionally, they need the ability to automatically detect if the customer has an app installed, and route the customer appropriately to the deep-linked content on the website or the app.

That is why we are excited to partner with Branch, the leader in deep linking. Combined with Blueshift’s personalization and recommendation capabilities on email, mobile apps and mobile websites, this provides the modern marketer a way to deliver seamless personalization to the perpetually connected customer.

Deliver frictionless experience with deep links

Deep links automatically take a user to in-app content or to the web if the app is not already installed. Mobile apps with deep links show 3x higher conversion. Blueshift supports deep links at scale in both email (for web and mobile) and SMS/push notifications and provides full attribution from first campaign to final conversion.

Here is an example of Blueshift’s native support for deep-linking:

 

Deepen engagement with personalization

Unlike other marketing platforms, Blueshift’s AI powered platform listens to every behavior in real-time and allows you to automatically add personalized content and products that are most relevant to the user in any channel. You can lead users to personalized in-app content or landing pages by adding deep links to your email, SMS or push notifications – driving higher conversions across. Track and optimize campaigns as you go with full attribution across all your channels.

With data, automation and AI – all in one platform, and integration with Branch.io, Blueshift allows you to deliver highly relevant and frictionless cross-channel experiences that lead to higher engagement, conversion and thereby, revenues.

The 4 Best Growth Marketing Campaigns That Delight Travelers

This series of blogs goes into detailed campaigns that growth marketers can run for specific industries. These campaigns are tailored towards goals and revenue that growth marketers are responsible for. Our third industry deep dive takes a look at the digital travel booking industry and campaigns specifically tailored for growth marketers to move users along the buying cycle fast and keep them coming back for more purchases.

The digital travel industry has come a long way in the past decade. What started from a handful of booking sites has grown into thousands of websites all fighting for attention through price comparisons, user experience, loyalty benefits, convenience, etc. Everyone is working hard to differentiate themselves from their competition. What they all have in common is thousands of people coming to their site everyday, ever changing inventory and prices, and millions of unique searches of what people are looking for. This creates the perfect recipe for growth marketers to cook up something new in digital engagement campaigns.

Below are 4 personalized email and notification campaigns growth marketers at digital travel companies launch to reduce churn. 

Abandoned Search

For your known users who make a search on your site and do not make a purchase, you can recommend fares based on their recent search with the dates and location from the search. This has to be sent out 1, 3, & 7 days after the search since it is a time sensitive search.

Add a Hotel/Car

A great up-sell campaign for customers who have recently booked a flight on your site is a personalized offer to add a hotel or car to their booking on those same dates based on the flight location/dates. This has to be executed immediately or between 1 and 3 days of the customer booking the flight.

Trending Getaway Deals

This is a great evergreen campaign for all your users to send them the latest and trending weekend getaway deals personalized based on their specific location. It can be sent on a weekly or monthly recurring basis. below is an example using a visitors location to deliver weekend getaways within relatively close distance to them.

Screen Shot 2017-03-01 at 12.11.38 PM

Location based recommendations

 

Promotions

Screen Shot 2017-03-01 at 12.04.36 PM

Promotional Sale

Another great evergreen campaign that requires little work on the marketers part is a promotions campaign. Airlines and hotels put out promotional offers every now and then and those can be used to send personalized offers of deals from nearby airports/locations based on the user’s location to your active customers on a weekly or monthly basis.

 

 

 

 

 


Watch out for more posts about growth marketing, and check out our comprehensive guide here for everything you need to know about the subject.

Growth-Marketers-Guide-to-Customer-Experience-720x180-blogfooter

Lifecycle Stages For Growth Marketers Part 2 – User Retention

Read Part 1 and Part 3 of our series “Lifecycle Stages for the Growth Marketer”.


Customer lifecycle is a term used to describe the progress of a customer as they go through consideration, engagement, purchasing, and maintaining loyalty to a product or service. It starts from the first time you get a user’s attention to your product and then keeping them as loyal customer.The customer lifecycle is often depicted a a circular cycle because the goal of customer retention is to get them to move through the cycle again and again.

Once you have the customer, it’s time to keep the customer. For Growth Marketers, much of their time must be focused on this area, otherwise you risk churning higher than normal amounts of users. (what is “normal” depends on your industry and business model.) In this stage, the focus is on Retention.

 

Enter Retention Campaigns

The second stage of the customer lifecycle is retaining users you already activated with targeted content in the form of reminders or recommendations to reduce churn. Retention is a more effective way of growing revenue because companies aren’t stuck attracting, educating, convincing, and converting potential customers. Retention is also a more sustainable business model for sustained growth because you are marketing to customer who have already expressed an interest in the product and engaged with the brand. In studies by Bain & Company, increasing customer retention by 5% can result in an increase in profits of 25% – 95%, and the likelihood of converting an existing customer into a repeat customer is 60% – 70%.

User retention gives growth marketers a lot of opportunity to deliver targeted content through many channels and in many forms. They can impact retention by creating delightful customer experiences through all their marketing channels on a 1:1 level using powerful reminders and recommendations. Lets dive deeper into what these reminders and recommendations can look like for growth marketers.

Screen Shot 2017-02-13 at 11.03.27 AM

Here is an example of 1:1 content recommendations in an email sent by a Blueshift customer

Reminders: 

  • Status in the Product: This type of reminder can be related to any incomplete activity in their account (e.g. “complete your profile” or “turn on push notifications”).
  • Weekly Activity Digests: Recurring personalized emails are a great way to keep active users engaged and staying on top of mind. For retailers this could mean sending a weekly email of new and trending items in their “Liked” categories or for media companies it can be trending content in the topics users are interested in.
  • Abandoner Re-Targeting: These reminders can be related to user activity such as browsed items or wish-listed products. For content businesses this can take the form of recommended content related to last viewed article or video.

 

Recommendations:

Screen Shot 2017-02-13 at 11.03.43 AM

Here’s an example of a catalog update message sent as a rich mobile push. All messages MUST be personalized!

  • Recommendations based on the customer’s Interaction Graph: The way users interact with your catalogue of products or content makes up their persona. This information is great for recommendations based on graphs created by users and other users. For example Twitter email notifications that give you suggestions on who to follow uses this same logic. The same idea can be used by retailers by leveraging data about people and products they have interacted with.
  • Recommendations based on affinity: Retail/E-commerce & media companies have large product catalogs or content. They have an even bigger data set of all the interactions users have with their catalog. This data can provide insights into preferences of users to certain categories, brands, authors, artists, price-points and more. The key to detecting user affinities is to not only look at individual user’s behavior, but also to normalize the behavior relative to other users. Growth marketers use these affinities to tailor marketing messages to every user on every channel, driving 3-10X higher response rates.
  • Recommendations based on change/updates in the catalog or app: Changes in your catalog of products or content, e.g. new arrivals in relevant categories, price drops on items that the user engaged with the website and app. These triggers are especially good for mobile push notifications since they are “newsworthy”.

Read Part 1 and Part 3 of our series “Lifecycle Stages for the Growth Marketer”.


 

Watch out for more posts about growth marketing, and check out our comprehensive guide here for everything you need to know about the subject.

Growth-Marketers-Guide-to-Customer-Experience-720x180-blogfooter

Lifecycle Stages for the Growth Marketer Part 1 – Activation

Customer lifecycle is a term used to describe the progress of a customer as they go through consideration, engagement, purchasing, and maintaining loyalty to a product or service. It starts from the first time you get a user’s attention to your product and then keeping them as loyal customer. The customer lifecycle is often depicted by an ellipse because the goal of customer retention is to get them to move through the cycle again and again.

A growth marketer’s prime objective is to drive user engagement with the product. The key to driving engagement is understanding the customer’s lifecycle stage and messaging them accordingly over time to keep them as an active customer. The first form of engagement is activating new customers. Activation is a stage when the user completes an action that indicates them getting value out of a product. This goal can be different for different business models e.g. an app like twitter might consider a user activated when they follow a certain number of other users within a given time-period; a retailer might consider a user to be active when they make their first purchase, or on a rolling basis.

Activation is the first step of the customer lifecycle when they fully experience the product or derived value from it. It is important to get users to activate faster because they can experience the product and see the value it provides. Users who don’t get activated quickly might never return since they never derive any value from the product in the time you have their attention. The core product experience is key to higher activation rates and growth marketers can help increase activation rates by extending the experience into marketing channels.

 

Below we go into some detail about the 2 ways in which growth marketers drive activation.

Welcome Series:

Welcome series from Flipboard

Welcome series from Flipboard

Almost every company or app has a welcome series of messages for activating and educating new customers. Such on-boarding emails have a 3X higher click thru rate than batch and blast emails. Growth marketers can take this strategy one step further by including the elements of product or merchandising in their emails or push notifications. A good example of this strategy is the app Flipboard. Their on-boarding process includes asking users about their interest in order to know what they like and personalize their experience in the app accordingly. This way they are able to onboard a new customer, educate them, and deliver a product that is personalized specifically for them. The welcome series is drawing the user deeper into the product and turning them into engaged users.

 

Abandoner re-targeting:

Guiding customers along their journey is very effective to activate them. This can also take the shape of re-targeting the user with a piece of the product or content if they do not activate the first time. Bringing a user back once they have abandoned is comparatively harder than connecting with first time visitors. For growth marketers to be successful at re-targeting they have to engage customers with very meaningful and compelling content to bring them back in the cycle. Abandoned cart items is an easy example of that or in the case of Flipboard it is the reminder of signing up with them to save your preferences in order to access it from the web or a different device.

Here retargeting is not only acting as a trigger to bring them back into the customer journey but also improving loyalty to the brand, stickiness of the product, and their overall lifetime value.

 


Watch out for more posts about growth marketing, and check out our comprehensive guide here for everything you need to know about the subject.

Growth-Marketers-Guide-to-Customer-Experience-720x180-blogfooter

Listening to your users: Inferring Affinities and Interests based on actual time spent vs clicks or pageloads

Personalized recommendations rely on the idea the you know the interests of your audience. In absence of explicit feedback, interests are generally derived from clickstream data: session and event (e.g. click) data. But given that sessions can be short lived (bounce) and clicks can be unintentional, they are unlikely to reflect true interests of your audience if you simply count them.

At Blueshift, we choose to actively follow along the individual’s storyline and extract intelligence from each event to gather insights of the user’s intent and interests, so we can provide better recommendations.

Let’s look at a real user example

In the table below, we see an actual clickstream of events from a user on blueshiftreads.com.

TimestampSession_idEventCategoryBook title
12:30:24session_id1viewBiography & Autobiography > Personal MemoirsEat Pray Love
12:31:29session_id1viewDrama > American > GeneralDeath of a Salesman
13:48:49session_id2viewScience > Physics > GeneralPhysics of the Impossible
13:49:02session_id2viewBiography & Autobiography > Personal MemoirsEat Pray Love
13:49:09session_id2viewHealth & Fitness > Diet & Nutrition > NutritionThe Omnivore’s Dilemma
13:49:19session_id2viewHealth & Fitness > Diet & Nutrition > NutritionThe Omnivore’s Dilemma
13:49:35session_id2viewPoetry > American > GeneralLeaves of Grass
14:09:47session_id2viewPoetry > American > GeneralLeaves of Grass
14:10:02session_id2add_to_cartPoetry > American > GeneralLeaves of Grass

This specific user interacted during two different sessions, browsing books from different categories. If we try to come up with the top categories for this user, based on total number of sessions, we get:

RankCategorySession count
1Biography & Autobiography > Personal Memoirs2
2Health & Fitness > Diet & Nutrition > Nutrition1
3Poetry > American > General1
4Science > Physics > General1

As you can see in the table above, Personal Memoirs is the top category while the three other categories tie to second-place (they have been alphabetically ordered in that case), but other tie-breaking rules can be applied.

Time spent ranking

At Blueshift, we developed algorithms to re-rank these categories according to the time the user actually spent on your products and categories:

RankCategoryTime spent
1Poetry > American > General1212
2Biography & Autobiography > Personal Memoirs72
3Health & Fitness > Diet & Nutrition > Nutrition26
4Science > Physics > General13

Here, we rank ‘Poetry > American > General’ above the other categories. Note that at the end of the original event stream above, the user actually did add the book from that category to the cart. Even if we would have ignored that event, our time based ranking would have indeed capture a category of interest to this user.

There’s more: decayed time spent

You should be careful not to rely on detailed information from a single user on a single day: if the user indeed bought the book he added to the cart, that might just be an indicator of no longer being interested in that specific category of products. Furthermore, you would want to adapt to changing user interest over time.

That’s why we implemented what we call a decayed time spent algorithm, that combines the time spent by users over a certain period of time (say last week) and that weighs recent time spent as more important to the ranking than time the user spent before (say 14 days ago).

Decayed weighting of recency this way allows recommendations to adapt quickly to shifting user interests when they are shopping during holidays and might be looking for gifts for others as well as themselves.

From user-level signal to site-wide signal

Many product recommendations are related to some site-wide top categories of products, like ‘top viewed’. Using our time based algorithms, we can better rank these top categories. Let’s look at another example from blueshiftreads.com where we show you a part (20-25 to be exact) of the top 25 most popular categories.

Using classical session counting, we obtain the following ranking:

categorysession count
Juvenile Fiction > People & Places > United States > African American5358
Juvenile Fiction > Girls & Women5291
Juvenile Fiction > Family > General5265
Fiction > Contemporary Women5215
Fiction > Thrillers > Suspense4971
Fiction > Mystery & Detective > Women Sleuths4804

However, when we rerank these categories based on actual time spent by the users, we see that ‘Juvenile Fiction > Girls & Woman’ drops from position 21 (above) to position 23 (below), even though it had 76 user sessions more in the 7 days over which this was calculated. User sessions are no guarantee for actual interest (i.e spending time).

categorytime spent
Juvenile Fiction > People & Places > United States > African American102164972
Juvenile Fiction > Family > General100447985
Fiction > Contemporary Women98897169
Juvenile Fiction > Girls & Women98340874
Fiction > Thrillers > Suspense91140081
Fiction > Mystery & Detective > Women Sleuths87372604

Furthermore, if we rank the categories using our decayed time spent, we see that ‘Fiction > Contemporary Women’ is actually ranked the highest (21) while it was the lowest (23) in the original list. This indicates that this category received the highest time spend by users in the most recent past.

categorytime score
Juvenile Fiction > People & Places > United States > African American28461106.29
Fiction > Contemporary Women28179308.93
Juvenile Fiction > Girls & Women28068989.26
Juvenile Fiction > Family > General27608048.02
Fiction > Thrillers > Suspense26102829.31
Fiction > Mystery & Detective > Women Sleuths24597921.38
Ok, why bother?

So why bother re-ranking? Well, most catalogs will exhibit a Long Tail in the distribution of popularity of their content: very few items will be very popular while lots of items will be very unpopular. No matter how you rank the popularity of the top-10 categories (sessions, clicks, time, …) out of a 1000 category catalog, these extremely popular categories will always on top. Just have a look at the top 20 categories from blueshiftreads.com:

blog_post_time_spent_top20

As you can see, the top 5 categories do a lot better than the rest. For most businesses there is a lot of value in promoting content from categories other than these few favorites. Therefore, if you can avoid down-ranking interesting categories for users and do this consistently over your whole catalog, you will be able to recommend products from the appropriate category to the users who care for it. In other words, you will avoid the pitfall of recommending an overly popular yet generic product to your users.

But time spent relates to sessions/clicks anyway?

Yes and no. It is true that more sessions correlate to more time users will spend on categories, but not to the same extent: a session length can range from a second to tens of minutes. Have a look at the next graph below.

What we see is the ranking of the 1000+ categories (on the X-axis) for blueshiftreads.com by popularity (on the Y-axis, logarithmic scale) over 7 days, in terms of 3 different metrics:

  • The blue line represents ranking by session count. It is very smooth because it really ranks all categories just in descending order of session count. This is the standard ranking.
  • The red line represents ranking by time spent by the users. It is equally smooth in the beginning (left) because it ‘agrees’ with the session ranking: as mentioned above, the top popular categories will always be on top. But quite soon, the line becomes spiky: the ranking disagrees with session count, and the spikes indicate that this ranking would reorder the categories in a different way (promoting different categories to the top).
  • The green line is the decayed time spent ranking: the same holds as the time spent ranking. This algorithm also disagrees with session count and would reorder lots of categories in the long tail to promote categories of interest to the user.

blog_post_time_spent_ranking_plot

This re-ranking is exactly what you should do to stop recommending the same popular categories to users that might have indicated (time) interest in other categories.

Avoid Personalization Pitfall # 5: Ugly Personalization!

In this series, we cover the common pitfalls all marketers face at some point when scaling personalization in their triggered marketing. From emails to mobile push notifications to SMS to display retargeting, the common platforms used today to market across channels begin to lose efficacy when organizations try to personalize their communications to an ever more complex and growing customer base.

Personalization Can Get Ugly



Watch this video to learn more about this subject from Brian Monahan, former CMO of Walmart.com 


Please, stop sending ugly emails…especially if you are going through the trouble of personlizing them. (Strike that, just don’t send ugly emails.)

Marketers using legacy systems often find that they are unable to combine “automation” with “creative” in these systems. As a result, some of the automated messages delivered by these legacy systems look ugly & “too automated” instead of personalized and delightful.

The inconsistency originates from using systems that are so complicated that the marketers have to pull in the IT and design team to execute a certain responsive ad or email and the creativity of the marketer is left behind. The customer should have a visually consistent experience as they move from one channel to another. Be it your website, app, push notification, or email, the same unique look should come across in every touch point.

Simple, Clean Designs Delight

In our experience with billions of emails and hundreds of email designs it is evident that the cleaner, simpler, and more seamless layouts get the highest CTRs and conversion rates. The goal of reaching out to customers is to delight them with a message that will bring them back to your site rather than drive them away with ugly looking emails or push notifications.

Here is an example of an email with a poor personalization design:

screen-shot-2016-10-10-at-11-25-20-am

This is a welcome email for signing up with Sheplers website. First thing you notice is that you cannot tell what they sell from this email. There is no mention of my name to make this personal. There are no images of products that catch your eye or a call to action. Overall this email does not provide much value to the customer.

Here is an example of a nicely designed, personalized email:

screen-shot-2016-10-10-at-11-34-15-am

This birthday email from LaserAway is a good way to bring back customers to your store or just staying on top of mind. There are exclusive offers and discounts to take advantage of specifically for the birthday week. There is an urgency and promotion that customers can act on.

When designing your emails, ask yourself if it is something YOU would like to receive. Or ask your team mates, friends, or your mom. Just please, don’t design ugly personalized emails.


Subscribe Now to this series
To learn more about all the common personalization pitfalls covered in this series, watch this VentureBeat Webinar that provides real world examples and fixes you can start using now.


  • Each update sent directly to you with extra tips NOT included in the blog posts
  • Access to the VentureBeat Webinar with former head of marketing at Walmart.com
  • Receive an audit of your current triggered activities with a marketing consultant

Personalization Pitfall #4: Poor Historical View of the Customer

In this series, we cover the common pitfalls all marketers face at some point when scaling personalization in their triggered marketing. From emails to mobile push notifications to SMS to display retargeting, the common platforms used today to market across channels begin to lose efficacy when organizations try to personalize their communications to an ever more complex and growing customer base.

Poor Historical View of the Customer



Watch this video to learn more about this subject from Brian Monahan, former CMO of Walmart.com 


Lifecycle marketing is a highly engaging way companies can re-activate or re-engage old customers. Using past interaction and transactions online, companies surface relevant products and promotions through different channels to influence a purchase. Sounds simple enough right? On the contrary having a 360 degree view of your customers over a long period of time and in real-time is very tricky for most businesses and our pitfall number 4.

Out with the old…

An old approach to this strategy has been to remarket to customers based on each item they browsed without taking their historical behavior into consideration. If a customer is browsing patio chairs, hammocks, and outdoor umbrellas, they are probably looking to furnish their backyard. Offering them 5 options of patio chairs might not be the best way to influence a sale.

personalization-pitfal-4-poor-histrical-view-of-customers-pic-1

 

personalization-pitfal-4-poor-histrical-view-of-customers-pic-2

Overcome Amnesia of Your Customers

Your product recommendation engine has to be smart enough to suggest “next best products” or “complete-the-look products” or a product in the same category or brand. Only personalized, smart product placement and recommendations can work to win back customers in the highly competitive market of today.

The key to re-marketing the right way is to connect every piece of user behavior and past purchase in real-time with a deep knowledge of the company’s catalog. Using a holistic customer view, marketers can provide a hyper-personalized story relevant to each user’s context.


Subscribe Now to this series
To learn more about all the common personalization pitfalls covered in this series, watch this VentureBeat Webinar that provides real world examples and fixes you can start using now.


  • Each update sent directly to you with extra tips NOT included in the blog posts
  • Access to the VentureBeat Webinar with former head of marketing at Walmart.com
  • Receive an audit of your current triggered activities with a marketing consultant