5 Ways Predictive Recommendations Can Transform Your Marketing

Increasingly, consumers are expecting completely personalized content when they’re online. While delivering 1:1 content to every user across every digital channel can seem next to impossible, bringing on predictive recommendations can transform everything from your user experience to marketing procedure.

1. Predictive recommendations keep customers online longer

We’ve all gotten sucked down the rabbit hole of excellent recommendations – a simple search turns into hours of browsing. Real 1:1 recommendations will leave your customers happily scrolling and discovering new products. This might lead customers to new products they wouldn’t have otherwise found on your site, but love nonetheless. 

2. Tailored recommendations make browsing a huge catalog easy

Sites with giant catalogs like Amazon may seem daunting to browse initially, their recommendations make it easy to find something you love. Blueshift customer, Urban Ladder, saw a 4x conversion rate from bringing on our recommendation capabilities.

3. Predictive recommendations create loyal customers

A big struggle of digital marketing is taking a traditionally offline market and adjusting it for an online experience, but it’s not as daunting as it seems. In the past, brick and mortar businesses that offered exceptional customer service and gave personal recommendations to each client experienced a high level of customer loyalty. Today, nothing has changed. Suiteness, a strictly online luxury hospitality company, has been able to step into the role of a travel agent and concierge for its customers – with stellar results

4. 1:1 recommendations can reheat customers who’ve fallen off

Some lost customers can seem impossible to win back. You throw the best promotions, and most clever and well thought out emails their way to no avail. 1:1 predictive recommendations can help provide real value to those tricky customers, and help lead them back to your site. A seamless recommendation engine that can cross over from email to website will play a major key in getting high-value, unengaged customers back on track and converting.

5. Predictive recommendations are responsible for revenue

Vouchercloud, the UK’s leading money-saving app, saw an 81% increase in revenue by using personalized recommendations across email and mobile push. 1:1 recommendations are no longer something that’s nice to have, they’re a necessity for driving growth. Learn more about Vouchercloud’s strategy here

Ready to learn more about Blueshift’s recommendation engine, and what it could do for your business? Contact our team, or learn more about our AI-powered recommendations here.

3 Tips to Avoid #Personalization #Fail Part 3

1:1 personalization isn’t just a lofty goal brands are considering attempting in the next few years. It’s here now, and consumers are starting to expect it as standard for their user experience. The biggest roadblock for marketers trying to deliver on those expectations? Sub-par tech inhibiting their customer-centric campaigns, which leads to comms that miss the mark. Check out some of the best #personalization #fail tweets of the last month:

1. Bring your data storage into the 21st century with NoSQL

NoSQL databases can better understand multiple data sources as compared outdated, sql databases. Conversely, traditional data storage makes it difficult for disparate data sources, such as your customer profile database and catalog database, to be understood holistically which leads to embarrassing fumbles like the one above. NoSQL databases can rationalize your siloed data in real time, which enables marketers to autonomously deliver relevant and accurate messaging to high-value customers.

2. Use AI that can target your biggest fans, not just Jane Doe

Don’t waste money going after shoppers who don’t want or need your products. Instead, utilize AI to forecast your most high-value customers and target these folks with personalized messaging that will keep them coming back for more. 

3. Soulmates, not twins

Use up-to-date insights and browsing patterns to influence personalized product recommendations, instead of vague selections based off of demographic insights. You never know who’s browsing! Seek out a comprehensive marketing platform that has the power to analyze website data in real time. So, families using one device, or just complex users, can get suggestions that impress and convert.

Ready to see how Blueshift helps customers avoid these common pitfalls? Connect with us today, or check out a few more tips on avoiding personalization failures here and here

 

Going Beyond the CDP: An Iterable vs. Blueshift Showdown

In our Going Beyond the CDP series, we break down how we compare to other Customer Data Platforms (CDPs). In this edition, see how we stack up against Iterable.

The main difference between Iterable and Blueshift is in the architecture. While Iterable is a solid solution for email-dependent organizations, the platform wasn’t built to support today’s rapidly changing landscape of marketing channels. Blueshift, on the other hand, was created by veteran marketing technologists who have been building evolving, scalable database architectures for decades. Let’s dig into the details.

1: Adaptive Customer Journeys

The ability to set up if/then scenarios inside customer journey flows is a standard but important capability for today’s marketer. For example, if someone reserves a hotel room to check in on Tuesday the 1st, then they will receive a How is your stay? push notification from the hotel manager on Wednesday the 2nd. But what happens if that customer changes their reservation?

Well, with Iterable, you’d have to rebuild the segment. Blueshift, on the other hand, automatically adapts the How is your stay? email date based on the new reservation. And what if you want to send multiple messages at different times related to the hotel reservation? One day before check-in, one day after check-in, two days after check-out, 11 months after check-out, etc. With Iterable, you’d need to build multiple customer journeys for each scenario, which can become a lot to maintain.

With Blueshift, that same process is taken care of behind the scenes. Our platform enlists an individual’s historical data to trigger event-based campaigns without requiring the marketing team to activate a specific promotion. In this example, the individual might receive a message that says something like, “You loved last year’s trip; let us help you book another great vacation.” This feature, which we call transactional modeling, allows you to connect and segment lifecycle events/behaviors through a common identifier.

21bd4d4-event_tr.png

2: Cross-Channel Identification

Iterable was built to solve email personalization challenges, but consumer expectations have grown far beyond the inbox. In order to be successful, today’s marketer needs to be just as savvy when it comes to mobile, apps, social profiles, and more.

Blueshift’s customer record doesn’t have a single primary key, but can be created and executed against any of the following keys: email, phone, device UUID, customer_id and Blueshift’s anonymous_id. This means clients can execute personalized messages to all of their customers, both known and unknown. For example, in Blueshift you can send mobile push messages to anyone that has a device UUID — and that’s it. There’s no need for an email address or customer id. Meanwhile, Iterable’s current documentation states the inability to send mobile push notifications, SMS, web-push, or the like to anyone without an email, as email is a required field.

Blueshift also stores behavioral data related to anonymous profiles so you don’t lose valuable data insights just because someone hasn’t signed in yet. Once there’s an identifiable event (email, phone, customer_id, etc), Blueshift combines all the anonymous data into a single identifiable user profile.

 

Cross Channel Identification

3: Platform Scalability and Stability

No system is perfect. Even the best of the best will occasionally experience hiccups, but those that are designed from the ground up to be scalable will be far more stable than those that aren’t (over the last 18 months, Iterable has experienced 61 incidents which degraded the performance of the application compared to Blueshift’s 6).

The way Blueshift handles scale is unique because our platform uses micro-services. Each service is tied to a different backend data store including in-memory, key-value, time-series based, reverse index, OLAP, log-based, etc. This means the Blueshift infrastructure is optimized for speed and flexibility by always ensuring the application hits the right data store for speed. Iterable is optimized for storage, which limits the amount of data it can process and retain along with how fast it can respond.

Ready to make the shift? Let us help you start out on the right foot by giving you a test drive of what’s possible.

Introducing the First-Ever Customer Data Activation Platform, Powered by Blueshift

We live in an always-on world where customers are increasingly interacting with brands across multiple touchpoints and “channels”. Not only have newer channels of engagement emerged, but more of the traditional broadcast channels have become “people addressable”. Ten years ago, we could not have imagined that banks would be engaging with customers over chatbots, or that TV advertising could be segmented and personalized. At the same time, traditional channels like email, SMS, direct mail, telesales and more have continued to stay relevant.

The Challenge of Intelligent Customer Engagement

Having so many people-addressable channels at their disposal gives brands the opportunity to drive true 1:1 Customer Engagement at scale. However, brands must overcome the challenge of delivering relevant and consistent messages on every touchpoint. This can be challenging with an ever-expanding set of tools and apps for each channel. Each of these channels and tools has a limited view of the customer, and that makes it challenging for marketers to intelligently engage customers. Common challenges include:

  • One-to-One: How can I personalize at a one-to-one level on each of these tools, merchandising the best offer or content for each customer at the right time?
  • Real-Time: How do I understand my customers and respond to them in real-time?
  • Cross-Channel: How do I deliver a consistent experience across touchpoints?

Without a complete view of customer data to aid these decisions, marketers often resort to simple batch-and-blast techniques that lead to irrelevance and incoherence across channels. How can brands escape a fragmented customer experience, or worse still, an experience that lacks any relevance to customers?

Activated Customer Data is the Glue

The problem lies in putting channels at the center of our processes rather than people. Marketers regularly build programs for paid media, email, and so on. But that approach means we’re always following (and attempting to catch up to) the customer. When we flip the order to focus on the customer first, the output becomes much more valuable. Customer data contains clues to customers’ intents and interests, but the data often lies dormant and disconnected from most channels. Activating this dormant data can help brands move from channel-centric to customer-centric.

In an always-on world, relevant customer engagement involves making millions of intelligent decisions in real-time, across multiple channels. Intelligent decisions that are made with a consistent view of customer data can help brands deliver a highly relevant and consistent experience for each customer. In other words, activated Customer Data is the glue that can make customer engagement relevant again. That is why I am excited about Blueshift’s launch of the Customer Data Activation Platform (CDAP) today.

Announcing the Customer Data Activation Platform (CDAP; “SEE-dap”)

The CDAP is a vision we have been working towards with our previous release, including AI-Powered Cross-Channel Journeys, Predictive Audience Syndications, and Live Personalization. Today, we released our App Framework that completes our vision. In simple words, the CDAP helps brands deliver intelligent customer engagement on every touchpoint on the tools they already use, by activating a full circle view of their Customer Data.

It’s not hard to imagine when and where a platform like this would be useful, but some key use cases include:

  • Personalize messages across engagement channels. Increase the relevance of messaging across online, offline, or proprietary custom built apps including email, mobile, direct mail, and chat
  • Increase paid marketing return on ad spend (ROAS). Identify high-intent customers through predictive modeling and keep them continuously updated in Google, Facebook, Twitter, Taboola, Linkedin, etc. through Blueshift Audience Sync.
  • Coordinate and optimize customer experience across channels. Trigger real-time, behavior-based messaging across customer touchpoints. Self-learning models optimize the journey flow.
  • Power CRM, analytics, and other systems with the latest user behaviors and dynamic segments. Automatically update and keep all your BI tools, analytics systems, CRM systems, and other technologies synced.
  • Streamline the customer experience across the full customer journey. Have customer service teams and messaging applications access a complete customer understanding and trigger real-time actions.

You can read the full press release here.

Winning through Data Activation

For years, brands have been investing in projects that help them “manage” data. While data management is a worthy goal, successful brands are more often defined by whether they can activate that data to drive intelligent customer experiences. Winners move beyond working for their data, and put their customer data to work for them.

Activating your customer data leads to a virtuous cycle for brands:

  • Customers interact with your brand and leave behind some first party data
  • Activating this data helps deliver personalized experiences
  • Personalization leads to trust with customers
  • The increased trust leads customers to interact more with the brand and share more data

This virtuous cycle of “data -> personalization -> trust -> more data” is the key to winning with today’s customers. In fact, a recent study by Blueshift and Techvalidate showed that the brands that activate more of their customer data also drive revenue success.

With the Customer Data Activation Platform, brands finally have the full set of tools they need for activating their customer data on every touchpoint with their customers.

Blueshift commits to supporting the Open Data Initiative

Blueshift is excited to announce support for Open Data Initiative sponsored by Microsoft, Adobe & SAP. The Open Data Initiative ensures data flows efficiently within organizations, between relevant roles and systems to build a unified single customer view that powers all customer journeys. A Single Customer View builds the foundation that powers personalized customer journeys using AI and predictive analytics.

The Open Data Initiative is based on three guiding principles:

  • Control: Organizations own and maintains complete, direct control of all their data.
  • Intelligence: Customers can enable AI-driven business processes to derive insights and intelligence from unified behavioral and operational data.
  • Open: A broad partner ecosystem should be able to easily leverage an open and extensible data model to extend the solution.

Blueshift’s mission is to empower marketers with an AI-first customer data platform to power cross-channel marketing. Customer profiles within Blueshift are updated in real-time by unifying cross-channel identities and behaviors to personalize user journeys. Blueshift’s industry leading AI powered customer journey helps marketers:

  • Audience: Determine “who to target?” with predictive audience scoring
  • Content: Compute “what to say to each user?” with ML powered recommendations
  • Cadence: And control the right timing and channel for message delivery with “when and where to message?”

Blueshift is committed to build support for Experience Data Model (XDM), the common format to exchange customer information including CRM, behavior, transactional and more between systems. Blueshift is built on noSQL technology that adapts to customer specified data models and natively supports JSON formats. With support for the Open Data Initiative, Blueshift customers will be able to import CRM, behavior & transactional data from Microsoft Dynamics, Adobe Experience Cloud & SAP, while quickly enhancing user journeys in these systems with Blueshift’s Customer Data Platform computed predictive scores and 1:1 computed personalizations.