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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.

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Location based recommendations

 

Promotions

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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.

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Top 4 Campaigns that Reduce Churn for Subscription Service Companies

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 second industry deep dive takes a look at the subscription service industry and campaigns for growth marketers to reduce churn and increase customer loyalty.

The subscription service model is unique compared to the conventional retail sales cycle. They measure their business with different metrics and have different goals. Some metrics that growth marketers at subscription companies are held accountable for are churn, up-sell, and win-backs. Much can be done to impact each of these metrics at different stages of the customer lifecycle. Here is a breakdown of personalized emails and push notification campaigns to use for reducing churn and increasing revenue for a subscription service company.

Churn Intervention: Marketing teams can use churn score rates to create a segment of at-risk customers based on their behavior or low engagement with the product. These customers can be sent personalized offers or incentives based on their purchase or browse history to continue the subscription on day 1, 7, and 30 days after they qualify for the churn list.

Subscription Upsell

Subscription upsell example from Birchbox. Prompting customers to gift a box for valentine’s day.

Subscription Up-sell: AI driven scoring can highlight customers with high up-sell propensity based on high engagement volume with the product. These highly engaged customers are great for incentivizing to switch to the next subscription tier since they are satisfied with their current tier. These messages can be sent out 1, 7, and 30 days after they show behavior of high up-sell propensity.

Abandoned Cart Email

Sense of urgency for customers who have not signed up.

 

 

 

 

Abandoned Cart: For the visitors on your site who have shared their email address but not made their first purchase or were in the middle of making a purchase but abandoned the session can be reached out to with very specific product they were looking at. Since these customers have not yet made a purchase it is imperative that the outreach be fast and timely (1, 3, 7 days after abandonment) or else they lose their intent to make a purchase or reason for considering the product in the first place.

Win Back Email

Offering a free snack and discount to churned customers

 

 

Win-back: For those hard to convince churned customers, growth marketers can offer personalized promotions based on an uplift strategy. The cadence can be 1, 2, and 3 months after churn since you don’t want to annoy these customers who are already out of the buying cycle. They no longer see the value in the service and it’s very hard to change their mindset while not putting them off.

 

 

 

 


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

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5 Must-Have Campaigns for Media and Publishing Marketers to Drive Growth

In this series of blogs I go 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 first industry deep dive is taking a look at the media and publishing industry.

Weekly digest email

Weekly Digest by grow by Acorns

The media and publishing industry is very content heavy and always changing. This high volume of time sensitive content gives growth marketers an opportunity to serve users fresh 1:1 content in many creative ways. With new content being added continuously and hundreds of thousands of people interacting with their content every hour, growth marketers have a huge amount of data at their disposal for engaging their readers and keep them coming back everyday. Below are the 5 top programs growth marketers in media and publishing industry use to drive higher customer engagement.

Personalized weekly digest: Recommend the best content of the week based on a user’s browsing history and attributes like location to all active users on a weekly basis.

 

Developing story alert

Developing Story Alert by Huffington Post

 

 

Developing story alerts: For news publications, updates to stories that users have previously expressed an interest or interacted with. This can be indicated by their browsing history or previous searches. Because of the news being time sensitive, the update should be sent within 15 min of the update.

 

Category affinity

Category Affinity Email by Flipboard

Category Affinity: Many media companies ask users about what topics they are interested in and want to see more of. Users can also show their affinity with a strong browsing and buying preference for a few categories. Recommend trending content from the categories preferred by the user on a weekly recurring basis.

 

Subscription Upsell: Convert freemium users to paid subscribers with relevant offers who have shown high purchase intent based on predictive scores. The cadence can be 1, 7, and 30 days after customer’s behavior indicates that they have a high intent.

 

Trending Content: Push out messages to highly active users recommending content that’s trending now in terms of views as soon as some new content becomes trending or newsworthy.

 


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

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Lifecycle Stages for Growth Marketers Part 3 – Win-Backs

Read Part 1 and Part 2 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.

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. Unfortunately, customers churn. Churn is a natural part of the process, however, as a growth marketer, you are responsible for bringing users and customers back.

Enter the Win-Back Campaign

Win-back campaigns are about re-activating churned customers or those who are at risk of churning. It is the typical customer lifecycle to become inactive due to the product losing its charm or relevance for the user. These tend to be the hardest to gain back but that’s the challenge growth marketers have signed up for. Growth marketers can deploy different strategies and campaigns to win-back churned customers and their effectiveness depends on how personal and creative you can be.Screen Shot 2017-02-20 at 10.27.34 PM

Traditional win-back marketing campaigns like “We miss you” and “Psst! Come back for 25% Off Your Entire Order” lack any kind of real-time data and insight into the customer. In addition, they actually don;t do much for the long term retention of a customer. Growth marketers have the ability to get more creative by providing actual value to users to get them to come back. (Don’t get us wrong, a discount/promotion code has a time and a place, but that strategy is often for short term gains.)

What is helpful about churned customers is that they are known users who have interacted with the product before in some form. This gives growth marketers large amount of data to use regarding the customer preferences to personalize all messages they send their way. This is an opportunity for growth marketers to think creatively on how to get a customer’s attention again.

 

An Example of a smart Win-Back Campaign

Here is a great example of Pinterest using known user attributes to suggest relevant people and topics to its churned customers to bring them back into the engagement lifecycle.

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Read Part 1 and Part 2 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.

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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.

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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:

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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.

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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.

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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.

Timestamp Session_id Event Category Book title
12:30:24 session_id1 view Biography & Autobiography > Personal Memoirs Eat Pray Love
12:31:29 session_id1 view Drama > American > General Death of a Salesman
13:48:49 session_id2 view Science > Physics > General Physics of the Impossible
13:49:02 session_id2 view Biography & Autobiography > Personal Memoirs Eat Pray Love
13:49:09 session_id2 view Health & Fitness > Diet & Nutrition > Nutrition The Omnivore’s Dilemma
13:49:19 session_id2 view Health & Fitness > Diet & Nutrition > Nutrition The Omnivore’s Dilemma
13:49:35 session_id2 view Poetry > American > General Leaves of Grass
14:09:47 session_id2 view Poetry > American > General Leaves of Grass
14:10:02 session_id2 add_to_cart Poetry > American > General Leaves 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:

Rank Category Session count
1 Biography & Autobiography > Personal Memoirs 2
2 Health & Fitness > Diet & Nutrition > Nutrition 1
3 Poetry > American > General 1
4 Science > Physics > General 1

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:

Rank Category Time spent
1 Poetry > American > General 1212
2 Biography & Autobiography > Personal Memoirs 72
3 Health & Fitness > Diet & Nutrition > Nutrition 26
4 Science > Physics > General 13

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:

category session count
Juvenile Fiction > People & Places > United States > African American 5358
Juvenile Fiction > Girls & Women 5291
Juvenile Fiction > Family > General 5265
Fiction > Contemporary Women 5215
Fiction > Thrillers > Suspense 4971
Fiction > Mystery & Detective > Women Sleuths 4804

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).

category time spent
Juvenile Fiction > People & Places > United States > African American 102164972
Juvenile Fiction > Family > General 100447985
Fiction > Contemporary Women 98897169
Juvenile Fiction > Girls & Women 98340874
Fiction > Thrillers > Suspense 91140081
Fiction > Mystery & Detective > Women Sleuths 87372604

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.

category time score
Juvenile Fiction > People & Places > United States > African American 28461106.29
Fiction > Contemporary Women 28179308.93
Juvenile Fiction > Girls & Women 28068989.26
Juvenile Fiction > Family > General 27608048.02
Fiction > Thrillers > Suspense 26102829.31
Fiction > Mystery & Detective > Women Sleuths 24597921.38
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.

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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:

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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:

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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.


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Practical AI for Growth Marketers

A.I has had a media resurgence in the recent past, thanks to the incessant coverage in every outlet and overblown hype for and against what it all means. Underneath the hyperbole there are real breakthroughs but also many challenges and practical considerations in using these innovations. This post by Crowdflower, a crowdsourcing platform used by many for improving the RoI of A.I projects puts it well when they say “A.I is a pragmatic technology that can be applied to solving today’s problems but you need to understand the limiting beliefs of A.I, and replace myths with truths”.

Growth marketers at B2C organizations specifically face formidable challenges in using A.I or machine learning in their day to day efforts. Data at their disposal spans many sources, updating via real time streams and likely runs into petabytes in size. Here are few practical considerations in realizing good RoI from your A.I project investments.

 

Simple vs Diverse data formats:

Today’s customers are tethered to their devices 24/7 and switch between them seamlessly. Advances in Big Data technologies like Hadoop have made it easy to capture raw data in diverse formats and store them across several different data stores usually called data lakes spanning SQL systems, NoSQL systems, flat files and excel sheets. As a growth marketer this is the raw gold mine you are working with and you should prioritize data capture in any format over shoehorning it to a particular data store or schema. A.I tools that you invest in should adapt to this mix of structured and unstructured data.

 

Real Time vs Batch mode:

The half life of consumer intent is getting shorter with each passing year, and customers expect “on-demand” experiences that are contextually relevant and personalized to them across every device. Growth marketers should prioritize simpler AI algorithms and processes that can adapt well to real time data than more complex batch mode solutions that may need several hours or days to execute. Pay close attention to training time it takes to build and deploy A.I models and how fast can they incorporate new data.

 

Complete vs Sparse data:

While it’s ideal to have every attribute and preference known about all users, in reality you will end up with incomplete or partially known data fields despite your best efforts. B2C growth marketers in particular should expect this from day one and invest in tools and solutions that adapt well to incomplete data. Take for example a user location, there may be a mix of user given location data, with device lat/long, ip to geo, inferences from content viewed or searches done and more. As a growth marketer you should prefer A.I tools that can adapt well to the mix of all this data and output best effort answers for widest user base than on few users with complete and clean data.

 

Size of training data:

Most A.I algorithms expect training data to be fed to them and the size and availability of training data is big obstacle to overcome to use them effectively. Certain class of A.I algorithms like Boosted Random Forests are better at adapting to the size of training data than Convolutional Neural Networks aka Deep Learning. Growth marketers should prefer those algorithms that can work with limited training data and have in-built sampling techniques to deal with disproportionate class sizes.

 

Black box vs Explainable Models:

A.I algorithms come in many forms, from easy to understand decision trees to black box complex ones like Deep Boltzman machines. Navigating the black boxes can be tricky, what works today cannot be said of tomorrow and need very careful tuning to yield short term results. Growth marketers should prefer AI algorithms that explain their outputs, and helps marketer understand various factors and weights given to them in realizing that output. Tools that iterate quickly and incorporate domain specific knowledge much more easily are likely to work better in the long term than hyper optimized black boxes with enticing short term yields.

When it comes to the nitty gritty of it all remember that A.I is no magic bullet but a practical tool to achieving your custom goals.

Keep calm and A.I on.

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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.

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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.


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