BLueshift solves the message overload problem for marketers. Monitor the frequency of all of your messages across all channels to avoid annoying your customers

Personalization Pitfall 3: Customer Message Overload

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.

Overcoming the Message Overload Pitfall

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

When you build out your company’s personalized marketing landscape you soon find your volume of messages increasing exponentially. As you set up re-engagement campaigns along the customer journey, the volume of messages across all channels can quickly add up to 10 or 15 different messages. Of course, that doesn’t mean you send them all 10 of these messages in one day or even a week. Customers feel overwhelmed if their inbox is flooded with one particular company emailing them again and again. Message overload is a sure way of ending up in your customer’s spam folder or worse, unsubscribing from all your communications. This rapid deluge of communications to your customers is our pitfall #3.

Don’t Be Annoying…

Message Overload across all channels is a personalization pitfall

Finding the balance between quality and quantity will save marketers from those dreaded mistakes of sending a customer too many messages in a day. But how do you make sure you aren’t sending to many messages across all your channels?

The way to achieve message zen is by smart segmentation of customers who fit a certain criteria based on their attributes and behavior on site. Behavior-based marketing resonates better than single trigger marketing because it tends to be more accurate rather than an in-the-moment action or even sloppy demographic focused bucketing. Grouping together customers who have shown similar behavior and sending a set of targeted messages that are personalized to their persona is a controlled way of using triggers on your site.

Think Beyond the Inbox…

“don’t simply focus on the amount of messages you send per channel, look at the aggregate of ALL of your messages sent through all of your channels”

Another way of working around the message overload problem is to build and monitor multi channel campaigns. Marketers constantly compete for inbox space along with numerous other brands. When’s the last time you looked at your inbox and didn’t feel like you were being yelled at by dozens of brands? A quick reminder to complete your purchase and checkout can easily be done via text message or push notification – abandoned cart campaigns are not simply just an email tactic. Dividing your messages across different channels can keep your brand name top of mind and limit annoying your customers. And remember, don’t simply focus on the amount of messages you send per channel, look at the aggregate of ALL of your messages sent through all of your channels. Otherwise, you still run the likely risk of annoying your customers with message overload.

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
  • Receive an audit of your current triggered activities with a marketing consultant

Blueshift challenges send time optimization with engage time optimization

Re-Thinking Send Time Optimization in the age of the Always On Customer

Many email service providers tout Send Time Optimization as an add-on feature and promise marketers that they can tailor their marketing campaigns to the exact time their customers are expected to open their emails. It’s tempting to take that at face value and think it’s a silver bullet to improving your customer engagement. Our internal research, after analyzing over a billion emails sent through the Blueshift platform over last year, has shown that in the age of smartphones and always on connectivity, the notion of “Send Time Optimization” needs some serious re-thinking.

Stop Optimizing to “Open Rates”

“look at full downstream activity and measure what windows of time their customers are more likely to follow through and complete specific goals”

Today’s perpetually connected customers are much more likely to have many more frequent bursts of activity around the clock than a recurring habit of opening their emails at a certain time of day or clicking onto sites or apps at specific hour. Then what does it mean to do “Send Time Optimization” for marketers? Instead of optimizing for immediate opens, marketers need to focus their attention and look at full downstream activity and measure what windows of time their customers are more likely to follow through and complete specific goals than when they open or click emails. The true measure of success should be specific conversion goals or sum total of time spent on your site or apps.

As a results-driven marketer ask yourself: “Would you rather have someone who opened a message, or someone who converted/made a purchase?”

Enter => Engagement Time Optimization

Blueshift’s recently released Engage Time Optimization computes windows of time for each user where they are more likely to engage fully, rather than optimizing for immediate opens or clicks. We look at the sum total of time spent by each customer over a long period of time and rank each hour in the day based on time spent and how deep in the conversion funnel they got to. You can access “hour affinity” for each user through the segments panel under “User Affinity” tab inside our application dashboard.

Re-Thinking Send Time Optimization in the age of the Always On Customer - look at engage time optimization to optimize your campaign sends to further down the purchase funnel


You can use these “hour affinities” like any other user affinity attributes during the segment creation and tailor campaigns to specific audiences. For example you can create segments of users who prefer “morning” hours by picking 5am to 8am or those who prefer “evening” hours by picking 5pm to 8pm or any other combination. We believe this offers a powerful alternative to traditional “Send Time Optimization” feature by tailoring the campaigns to the customers based on their full funnel behavior than on immediate opens or clicks.


If you’d like to see a demo or request more information on Engagement Time Optimization, contact us via our site or email us at


Personalization Will Make or Break Holiday Season Campaigns

Customers demand respect from retailers. They ask simply for organizations to remember who they are as an individual consumer from a transaction and a behavioral perspective — otherwise, they are likely to purchase less frequently, or, more than likely, churn to a competitor who does understand them and communicate with them better at that individual level.

Personalize, personalize, personalize!

This has been the mantra of marketers looking to communicate with their customers at a highly relevant and engaging way. According to the latest report by Accenture covered by MediaPost:

  • 56% of respondents acknowledged they were more likely to shop at a retailer that recognized them by name
  • 65% of consumers expressed a preference for retailers that remembered their purchase history
  • 58% of respondents were more likely to shop at stores that offered relevant recommendations based on past purchases or preferences



The need for smarter cross-channel personalization…

It’s important to point out that marketers are being asked to personalize across all channels, not just one or two. In fact, as the Accenture report highlighted, less than 50% of consumers completed a purchased based on an on-site product recommendation. The perpetually connected consumer now enters the buying cycle from a number of channels and touch points: email, Facebook, SMS, mobile push notifications, in-app personalizations, and numerous others.

And forget about flooding a consumer with a higher number of product recommendations. The “Quantity over Quality” tactic is similar to annoying batch and blast techniques used within emails by out-of-touch marketers. Filling a page or a communication with a dizzying number of recommendations only annoys and splits the buyers attention away from products that they are more likely to purchase. According to the report, almost 40% of respondents admitted to abandoning an online shopping experience altogether because of an overwhelming choice of recommendations

The “Burden of Choice” is in the hands of the brand. Brands must serve only the best recommendations to the right person built through predictive algorithms that sift through the dozens or even hundreds of “best products” that could be delivered to the consumer and transform that into the best few.

Read the full article on MediaPost.

Obama on Technology, AI and an Optimistic Future

“This year, Artificial Intelligence will become more than just a computer science problem. Everybody need to understand how A.I. behaves.”

Recent advances in computer science and AI (more specifically advances in building and running large convolutional neural networks) have given a fresh fodder to the age old debate on how technology is replacing workers and making us all obsolete. The current political climate only amplifies the anxiety and generates FUD (Fear, Uncertainty, and Doubt) about our collective future. So it’s very refreshing to see President Obama re-framing the discussion in this Wired article and talking about common humanity and a confidence in our ability to solve problems. If one can ignore the media hype and peek below the surface there are real opportunities to build solutions to many seemingly intractable problems.

Machine learning, data mining and deep learning techniques can nudge us to lead healthier lives, change our habits and build stronger communities. Imagine AI powered tools that remind us in context of whatever we are doing in our daily lives to consider factors that we may have missed, overcome biases in thinking fast and slow, present information in ways that helps us build better financial portfolios that are in our long term interests, prevents us from being defrauded or phished or scammed online, helps us communicate with every one one the planet crossing language boundaries and more. That’s the optimistic future we can aspire to and it’s refreshing to see this possibility being talked about.

President Obama chatting with Ito and Scott Dadich

President Obama chatting with Ito and Scott Dadich

Read the full article on

What is Programmatic CRM? [Infographic]

Programmatic CRM is a technology that enables marketers to be customer-centric and leverage real-time behavioral data to reach every customer on an individual level throughout all of your marketing channels. Bringing Programmatic CRM into your marketing stack enables marketers to finally automate the delivery of consistent and delightful user experiences on every channel with true scalability and greater results.

Reach the perpetually connected consumer across all channels at the moment they are most inclined to engage with you brand.

The building blocks of Programmatic CRM

Programmatic CRM is built up a number of key components that work together to Engage with Segments-of-One:

  • Real-Time Triggers to engage customers based on their actions
  • Cross-Channel Reach to be customer-centric, not channel-centric
  • Personalized Recommendations to tailor recommendations to user behavior
  • Dynamic Audiences for segments that update with every customer interaction
  • Measurability to deliver end-to-end reporting on engagements and conversions


Isn’t it time you stop marketing to stale databases built of attributes and demographics?


Behind-the-Scenes: Real-time segments with Blueshift

(Here is a behind the scenes look at the segmentation engine that powers Programmatic CRM.)

Real-time segmentation matters: Customers expect messages based on their most recent activity. Customers do not want reminders for products they may have already purchased or messages based on transient past behaviors that are no longer relevant.

However, real-time segmentation is hard: it requires processing large amounts of behavioral data quickly. This requires a technology stack that can:

  • Process event & user attributes immediately, as they occur on your website or mobile apps
  • Track 360-degree customer profiles and deal with data fragmentation challenges
  • Scale underlying data stores to process billions of customer actions and support high write and read throughput.
  • Avoid time consuming steps of data modeling that require human curation and slows down on-boarding

Marketers use Blueshift to reach each customer as a segment-of-one, and deliver highly personalized messages across every marketing channel using Blueshift’s Programmatic CRM capabilities. Unlike previous generation CRM platforms, Segments in Blueshift are always fresh and updated in real-time, enabling marketers to respond to the perpetually connected customer in a timely manner. Marketers use the intuitive and easy to use segmentation builder to define their own custom segments by mixing and matching filters across numerous dimensions including: event behavioral data, demographic attributes, predictive scores, lifetime aggregates, catalog interactions, CRM attributes, channel engagement metrics among others.

Segments support complex filter conditions across numerous dimensions

Segments support complex filter conditions across numerous dimensions

Behind the scenes, Blueshift builds a continually changing graph of users and items in the catalog. The edges in the graph come from user’s behavior (or implied behavior), we call this the “Interaction graph”. The “interaction graph” is further enriched by machine-learning models that add predicted edges and scores to the graph (if you liked item X, you may also like item Y) and also expand user attributes through 3rd party data sources (example: given the firstname “John”, with reasonable confidence we can infer gender is male).

Blueshift interaction graph

Blueshift interaction graph

The segment service can run complex queries against the “interaction graph” like: “Female users that viewed ‘Handbags’ over $500 in last 90 days, with lifetime purchases over $1,000 and not using mobile apps recently and having a high churn probability” and return those users within a few seconds to a couple of minutes.

360-degree user profiles

For every user on your site/mobile app, Blueshift creates a user profile that tracks anonymous user behavior and merges it with their logged-in activities across devices. These rich user profiles combine CRM data, aggregate lifetime statistics, catalog-related activity, predictive attributes, campaign & channel activity and website / mobile app activity. The unified user profiles form the basis for segmentation. A segment query matches these 360 degree user profiles against the segment definition to identify the target set of users.

360-degree user profiles

360-degree user profiles in Blueshift

Multiple data stores (no one store to rule them all)
The segmentation engine is powered by several different data stores. A given user action or attribute that hits the event API is replicated across these data stores including: timeseries stores for events, relational database for metadata, in-memory stores for aggregated data & counters, key-value stores for user lookups, as well as a reverse index to search across any event or user attributes quickly. The segmentation engine is tuned for fast retrieval of complex segment definitions compared to a general purpose SQL-style database where joins across tables could take hours to return results. The segmentation engine leverages data across all these data stores to pull the right set of target users that match the segment definition.

Real-time event processing

Website & mobile apps send data to Blueshift’s event APIs via SDKs and tag managers. The events are received by API end-points and written to in-memory queues. The event queues are processed continuously in-order, and updates are made across multiple data stores (as described above). The user profiles and event attributes are updated continuously with respect to the incoming event stream. Campaigns pull the audience data just-in-time for messaging, which result in segments that are continuously updated and always fresh. Marketers do not have to worry about out of date segment definitions and avoid the “list pull hell” with data-warehouse style segmentation.

Dynamic attribute binding

The segmentation engine further simplifies onboarding user or event attributes by removing the need to model (or declare) attribute types ahead of time. The segmentation engine dynamically assesses the type of each new attribute based on sample usage in real-time. For instance, an attribute called “loyalty_points” with a value of “450”, would be interpreted as a number (and show related numeric operators for segmentation), while an attribute like “membership_level” with a value of “gold” would be dynamically interpreted as a string (and show related string comparison operators for segmentation), or an attribute like “redemption_at” with a value like “2016-09-23” will be interpreted as a timestamp (and show relative time operators).

Several Blueshift customers have thousands of CRM & event attributes, and are able to use these attributes without any data modeling or declaring their data upfront, saving them numerous days of implementing data schemas in SQL-based implementations.

The combination of 360-degree user profiles, real-time event processing, multiple specialized data stores and dynamic attribute binding, empowers marketers to create always fresh and continuously updated segments.


Personalization Pitfall #2: Old-School Linear Customer Journey

Marketers rely on customer journey mapping to optimize what customers see every step of the way. But with the rise of multiple devices and the perpetually connected customer (a.k.a “perpetuals”), it is becoming harder for marketers to define the different ways a customer interacts with content or products. In today’s increasingly complex environment, marketers must change the way they conceptualize a path to purchase and adopt a new paradigm — real-time context.

Perpetual’s can’t be pigeonholed into old-school linear journeys. They carve their own path to purchase and the number of possible paths to purchase increase exponentially due to multiple devices and different intents. Perpetuals too often turn to their phones in search of information, whether they’re at the gym, commuting to work, or shopping for groceries. Google refers to these spontaneous instances of discovery as micro-moments, and they’re opportunities for brands to meet their customers at moments of intent.

An example is that Jack could be leaving the gym and thinking about buying another pair of gym shorts which he searches for on his phone and places in his cart. A few hours later, he remembers he has to go to a friend’s birthday in a week and starts looking at gift options for them on his laptop. Tech savvy marketers have to be able to react to the changing needs of customers like Jack as his intent changes, in real-time, across different channels, and with the right content.

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

Personalization Pitfall 1: Outdated messages

Common Problems Faced when Scaling Personalization – Part 1

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. The problems stem from generic/ out-of-the-box triggers, poor segmentation, outdated information, lack of real-time processing, and disconnected channels, to name a few.

If these pitfalls aren’t addressed in your marketing strategy, you risk pushing customers away, often to your competition. By building a better personalized customer experience across all channels, you build more loyal returning customers. Customers today demand 1:1 communication and a high degree of relevancy in any marketing message.

Subscribe Now to this series

  • 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
  • Receive an audit of your current triggered activities with a marketing consultant

Personalization Pitfall #1: Outdated messages

According to Forrester Research, “Trigger based email marketing campaigns can generate 4x more revenue and 18x greater profits”. Triggered messages are known to be 5 times more responsive than batch and blast campaigns, which makes triggered marketing communication very attractive to marketers. As simple as it is to send out triggered messages, it is also that much easier to get them wrong. Triggered messages are personalized based on a user’s engagement with your website or mobile app. The timing and content has to be precise because any delay in the data or message can lead to outdated messages being sent to your customers who then in-turn will unsubscribe because they feel spammed, and will often take to social media to voice their opinions:






One of the most common pitfalls we hear about from marketers using triggers is their customers getting outdated messages through retargeting. It’s very common for customers to receive a display ad or email about a product they have already bought; or a recommendation for a product that has nothing to do with their purchase history or recent interaction with the brand. “54% of consumers would consider ending their relationship with a retailer if they are not given tailor-made, relevant content and offers.” Retailers can no longer afford to run outdated triggered marketing through their legacy systems. It pushes customers away and shows a lack of respect for your customer’s buying habits.

Here is a small recording on this very issue from our webinar with VentureBeat, “How to become a personalization ninja and delight every customer“:

become_a_personalization_ninja_with_blueshiftTo 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.

Subscribe to this series for instant access to the full video.>>

Focus on Real-Time Data

Most retargeting campaigns are based on customer actions, browsed products and abandoned cart being some very common triggers. But if the systems of record (CRM) and systems of action (ESP, DSP, Facebook retargeting, etc) are not synced in real-time when a customer makes a purchase, this faulty cycle will keep repeating itself. Unless customer data is updated in real-time, there will always be outdated information being presented in display ads or emails going out to customers.

Personalization Pro Tips:

Blueshift has worked with several marketing leaders that have scaled their personalized marketing programs to deliver engaging personalized user experiences. Here are our top tips to get the most out of your personalization efforts:

  • Don’t settle for Near Real-Time: For the best customer experience, use systems that enable you to personalize with true real-time information.
  • Remain goal oriented: Understand your key performance indicators and how they affect the entire campaign, not a single send.
  • Personalize across channels: Use multiple marketing channels to scale your marketing program, instead of limiting it to email.

Say AARRR on “Talk Like A Pirate Day”

It’s International Talk Like a Pirate Day. You can celebrate the day as a growth marketer, by saying AARRR & reminding yourself of Pirate Metrics for growth:




Market to Verbs, not Nouns

Marketers have always believed in targeted marketing. In the past, targeting has meant building a database of customers and their attributes, especially demographic attributes like first & last name, gender, location, and more. In this notion of database marketing, the databases describe nouns, like customers and products, and attributes of these nouns.

I wrote an article today in CMS Wire on how marketers should market to verbs, not nouns. Today’s leading edge marketers are finding that targeting based on nouns is outdated in the world of “Perpetually Connected Customers”, who are accessing information every second on web & mobile. The Perpetually Connected Customer’s actions & behavior are an indicator of their needs and wants desires, and marketers are confirming something that we have always suspected: that customers are multi-dimensional, and behave differently at different times.


Why are verbs more important than nouns in targeted & personalized marketing? And why is their importance increasing over time? The two primary drivers are related to how customers have changed over the recent years, and how media has changed:

  • Perpetuals are not the same consumer from moment to moment: Perpetuals’ willingness to consume, changes depending on what they are doing. When describing people or customers, you could choose to describe them using static attributes like location or gender, that don’t change over time. However, people are multi-dimensional, and their interests and desires shift over time. Understanding the customer’s stream of actions is the only way to react to the changing desires of the perpetually connected customer.
  • The death of mass-media and the drive towards 1:1 personalization: Customer attention spans are shifting away from mass-targeted media (like broadcast TV) towards truly personal mediums where people consume content on their own terms. Correspondingly, marketers and advertisers need to shift their framework away from describing people in ways that are hangovers from the mass-media world –using attributes like gender, location, education etc. Instead, marketers need to concentrate on understanding the set of actions that truly set every individual apart, as no two customers rarely ever follow the same sequence of interactions with the same items.

To read more, head over to CMS Wire.