Friday Five

Friday Five AI in Marketing: AIMythBusters, StitchFixIPO, GetAIReady, AIForMarketers, AI&ML

Welcome to our Friday Five. Each week, our goal is to give you a run-down on 5 of the top stories on the topic of AI in Marketing. Think of this as that TL;DR of those stories you meant to read or might have missed.

Marketing AI: A win-win

AI, machine learning and algorithms sound intimidating? How does “knowing which customers to target? Or which customer is likely to convert?” That is exactly what AI and machine learning can help marketers know.

“Predicting the possibility of a given prospect to convert

Predicting at what price a prospect is likely to convert

Identifying customers that are most likely to become repeat buyer”

Learn more on how AI can help marketers win:win


AI Myth Busters: AI Will Usher In An Era Of Extreme Personalization

Sticking to our theme of myth busting AI for you every week. Here are they are again. AI is too complex? Are you afraid AI will take away your job?

“In reality, AI isn’t as complex, scary or confusing as James Cameron and “The Terminator” would have you believe. Many of today’s AI-powered platforms are designed to plug and play into existing martech stacks, eliminating the need to rip and replace incumbent technology systems”

Read on to bust your myths about AI


Are You Ready to Make The Shift to A.I.?

Now that your myths are busted? Are you ready to shift to AI? IDC forecasts a 54% growth in Marketing spend on AI software over the next four years to more than $2 billion in 2020. Why? Because AI and machine learning (ML) can help marketers identify patterns to guide better marketing decisions.

“Data is unquestionably the domain of A.I.”

Collecting data and fixing data silos are the first steps to get started with AI. Read more on how to get started with AI


4 Ways You Could Be Incorporating Artificial Intelligence Into Your Marketing Strategy

Have you ordered coffee from Alexa? It is fun at first, and soon a habit that saves time in our busy lives

“As customers become accustomed to AI-powered solutions like Starbucks’ Alexa offering, they’ll expect the same from their local businesses.” That means it’s more important than ever to start considering how artificial intelligence can positively impact your business model.

Processing data, personalization, customization and pricing – read more on how you could be incorporating AI into your marketing strategy


From Blueshift: 3 Lessons from StitchFix IPO on AI and personalization

And finally, from Blueshift. And we say, Human+AI = Magic!” Why? See StichFix.

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

The guiding philosophy is that every customer is different and every experience should be different. At StitchFix, no two shipments are the same and the algorithm learns more about you. Read more about how StichFix leveraged AI and data science to deliver personalization to every user.



AI and Human is Magic

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”.

Re-engagement Campaigns

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.

Friday Five

Friday Five: #Human+Machine #FinTech #AIFirst #12_Ways_to_Boost_CX #UK

Welcome to our Friday Five. Each week, our goal is to give you a run-down on 5 of the top stories on the topic of AI in Marketing. Think of this as that TL;DR of those stories you meant to read or might have missed.

Human+Machine and CX+AI: Insights from Forrester CXSF

“All of you in this room are slowly and inexorably going out of business.” – George Colony, Founder & CEO, Forrester

No, it is not the robots-coming-for-your-job kind of going out of business. But,

“Customer is becoming an empowered force in a changing economy. Two factors that will determine success in this new era: 1) Customer experience and 2) Artificial intelligence”

Insights from Forrester’s day 1 of CXSF event. One more thought provoking quote from the event, “Personalization, generally, sucks. I don’t understand why. I’ve been in this business for 20 years and I’m seeing little more than recommendations. There’s no longer an excuse.” – RJ Pittman, eBay Chief Product Officer

What is your excuse? For more insights on AI, the future with Human+Machine and how customer experience and AI  will determine your success, tune in to Forrester CXSF event.


12 ways AI could boost your customer relations

AI based marketing, personalized website experiences, personalized emails, personalized upsells and cross-sells, predictive analyses – just a few ways AI can boost customer experience. Isn’t customer experience the one thing that matters to win today?

“As more companies start sending emails to their customers, forward-thinking marketers are going to want to stand out through further personalization. If you only send the content that the customer is interested in, they are more likely to click and read the emails.”Jared Atchison, WPForms

AI enables you to do personalized marketing across all channels. See 12 ways AI could boost your customer relations


AI for financial planning

Consumer finance is characterized reams of data. Processing this from multiple sources can take months.

“If the internet is the superhighway for the rapid transit of information, then artificial intelligence is the E-ZPass that helps you become even faster and more efficient.”

AI helps to know so much about a client — what they want and what they need — you can be exponentially more effective in creating the experience that will move them forward in their financial life and drive your firm’s success. See more on the new opportunities AI brings for financial planning. Watch how a forward thinking consumer finance company, #LendingTree uses AI to give individualized value to every user.


UK perspective on Artificial intelligence: Hype, hope and fear

A Welsh company is using AI to detect North Korean bio-weapons. Governments are taking deep interest in the possibilities with Artificial Intelligence.

“We are accustomed now to technology developing fast, but that pace will increase and AI will drive much of that acceleration.”

Among all the hype, hope and fear, a UK commissioned report estimated that #AI could add an $814bn to the UK economy in the next 20 years and an earlier study by McKinsey estimates an addition of $126B to US economy in next 10 (not 20) years. Read more from this report on how UK sees potential in AI.


Blueshift in the news: AI-first marketing could help brands perfect the customer experience

And finally, Blueshift in the news. Curious why so much hype about AI now when it seems to exist forever.  Today’s AI moved from edges to the core.  What does that mean? Hasn’t it moved from simple driver-assist to the center of self-driving cars?

“According to Gartner, customer experience is the new battlefield for competitive advantage. In the AI-first world, the only survivors on this battlefield will be the ones who embrace AI at the core of their marketing and customer experience strategies.”Vijay Chittoor, Blueshift co-founder & CEO

See how AI-first marketing could help brands perfect the customer experience.


Big Target is the wrong target for Facebook Retargeting

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.


Friday Five

Friday Five: AImyths, Putin_And_Obama_About_AI, AIQuotes, MITStudy, IconicFirms, Blueshit_AI_Patent

Welcome to our Friday Five. Each week, our goal is to give you a run-down on 5 of the top stories on the topic of AI in Marketing. Think of this as that TL;DR of those stories you meant to read or might have missed.

12 AI Quotes Everyone Should Read

Do you believe Alan Turing was true in his prediction below? Imitation Game, a story about his life is one of my all time favorite movies and has several quote-worthy quotes that I would recommend you to check out about machines, AI and life.

“I believe that at the end of the century the use of words and general educated opinion will have altered so much that one will be able to speak of machines thinking without expecting to be contradicted.” (1950)” – Alan Turing, 1950

AI as a key to unlock power” – Vladimir Putin

Wonder what Putin means by that. Interested in what other leaders have to say about AI? Read what Obama, Elon Musk, Mark Zuckerberg, Larry Page and Sergey Brin said about AI.

MIT Study Reveals How ‘Iconic’ Firms Use AI

Guess what’s holding companies that invested in AI from fully deploying it. The answer is, not sharing customer insights across the organization. If companies want to put customer experience at the forefront, sharing customer data should be a high priority.

The first benefit is in “a step-change increase in efficiency: by gathering customer data (a time-consuming process” – Felix Liu, Alibaba

See more on how iconic firms embrace technology to improve CX from the MIT report: Getting to Iconic: How world-leading brands balance talent and technology for CX excellence.

Mythbusting the future of AI in financial services

Third week in a row we are feature AI myth busters. It is a no wonder with all the hyper around it. It is a wait-and-watch to see how partnerships and AI will transform financial services. Meanwhile, what caught my eye in this article is,

AI is about solving specific problems using data and fancy maths, and isn’t even close to abilities like self-awareness, common sense and creativity

Read more on how AI can influence the financial industry and check if your AI myths are answered in this post

How to become savvier with your marketing by implementing AI techniques

Like the article points out, Netflix, Amazon and Google have nailed customer experience and predictive recommendations with AI. From chatbots and customer engagement to content curation, AI can help marketers improve ROI

Artificial Intelligence powered tools can gather data, build a predictive model, test and validate real customers. When these techniques are combined, customers will become more engaged and loyal leading to higher lifetime value and increased company profits.

Read more on how to become savvier with artificial intelligence

Blueshift in the news: Blueshift Receives Patent for AI-Powered Marketing

And finally, we are very excited to share that Blueshift has been awarded a patent for innovation in AI powered marketing to deliver real-time 1:1 customer experiences at scale

Brands continue to generate more and more customer data in the form of behavioral ‘events’, that represent customer interactions on digital, mobile and social channels. AI is the key to activating this fast moving stream of event data and delivering segment-of-one personalization on every channel” – Manyam Mallela, Blueshift co-founder & Chief AI Officer

Read more on how Blueshift is innovating to translate customer data into 1:1 experiences.

Activating Customer Data

Activating Customer Data with Graph Technology

Graph technology powered customer experience

What do Netflix, Amazon, LinkedIn, Facebook, and Google have in common? While they all serve different needs, they do that in a unique way by delivering an individualized experience to hundreds of millions of users at scale. From a user’s perspective, these brands seem to have an uncanny ability to have a 1:1 conversation, and understand each user’s unique tastes and preferences. In fact, no two users have the same experience with any of these brands. By delivering unique personalized experiences, they have gained incredibly loyal users that keep coming back for more and have become dominant in their respective categories.

But, what technological advantage do these companies have that gives them the ability to deliver individualized experiences at scale? If you look under the hood, unlike the previous generation of consumer companies that built customer experience on traditional IT systems, these leaders leverage a graph-based technology stack.

Before we continue, let me outline what we mean by a graph-based technology stack.

Let’s use Netflix as an illustration.

Behind the scenes, Netflix has built one of the largest graph of its users and their content preferences. Each time a user views, rates or adds a movie to a watch list, Netflix updates this graph with the user’s behavior in near real-time. Subsequently, Netflix uses this graph to deliver a rich user experience that recommends the next movie for a user to watch based on techniques such as what’s trending in user’s location, similar user preference, or a user’s affinity to a certain genre based on past behavior. Netflix delivers this experience to the user on all channels including apps, website and email. Every user engagement enriches the graph for all users. So the next time a user logs in, Netflix can further personalize the experience for the user, keep churn low and keep users coming back for more.


Personalized Netflix home page for a user


Netflix user movie taste graph captures user intents and interests.

Similar interaction and data graphs power the consumer experience of Facebook, Amazon, LinkedIn and Google. In the future we believe every digital company will have such an interaction graph. While the technology obstacles required to build, maintain and use such graphs are formidable, the existence of data underlying the graph is undeniable no matter which industry you are in.

Challenges in building an interaction graph

If data is readily available, then why are more brands not able to deliver an individualized and relevant user experience? Past efforts to build individualized experiences using an enterprise data warehouse have failed due to slow ETL processing, long query times and the disconnected nature of engagement channels that require sub-second response times for accurate decisioning. By the time user data is computed and activated, it is very likely stale and out of date, resulting in user annoyance instead of delight. Some forward thinking companies have recognized the flaws of a data warehouse driven approach, and embarked on building a user graph in-house using open-source graph databases.

Building such a graph in-house has several challenges that include:

  • Real-Time: It requires updates in real-time as users interact across website, mobile, email and other channels. The graph should support highly concurrent, low-latency writes, and high throughput search/queries.
  • Cross-Device: Users may not always be signed in and may be using multiple devices, which requires tracking plus merging anonymous and known behaviors across devices. The graph service needs to capture device identifiers, cookies, first party data and 3rd party data to enable deterministic and probabilistic profile tracking and merges.
  • Learning: The graph needs to be enriched with real-time user intents and long-term interests derived from behaviors. This requires algorithms suited for online learning and models that update in near real time with new data.
  • Scale: Depending on the size of the user base and content catalog, the graph may need to scale to processing billions of edges resulting in terabytes of data, while supporting sub-second query responses.
  • Data Fragmentation: On-going ETL and building connectors to deal with data fragmentation and evolving data schemas makes implementations brittle.
  • Resources: Budget and resourcing constraints to hire a team of engineers, analysts, data scientists and managers to build the technology stack and maintain integrations.

How we use graph technology at Blueshift

Blueshift’s next generation customer data platform is powered by an interaction graph: A real-time undirected graph created using 1st party behavior data from every engagement touch-point. Blueshift’s customer data platform captures all your user interactions in real-time and is available across every channel. Blueshift’s Interaction Graph powered CDP is usable out of the box, and companies can onboard terabytes of data in just few days.

Leading digital brands such as LendingTree, BBC, IAC and Udacity are using Blueshift’s Interaction Graph powered CDP to engage their consumers with a unique individualized customer experience across every touch point and seeing a significant lift.

Ready to learn more about Blueshift’s Customer Interaction Graph, contact us today.

In a follow up to this post, we’ll talk about the algorithms and systems required to build the interaction graph, stay tuned.

Blueshift Awarded Patent

Blueshift’s Patent Brings Industry-Changing Innovation to AI-Powered Marketing

We are very excited to share that Blueshift has been awarded a patent for innovation in AI powered marketing to deliver real-time 1:1 customer experiences at scale: Patent No. 9779443 from the United States Patent and Trademark Office for “EVENT-BASED PERSONALIZED MERCHANDISING SCHEMES AND APPLICATIONS IN MESSAGING”

The patent aligns with our vision to be the leader in helping companies deliver unique experiences to their customers with cutting edge technology built for forward thinking marketers.

“Customer Experience is the new battlefield for competitive advantage. In an AI-first world, the only survivors will be the ones who embrace AI at the core of their marketing and customer experience strategies.”Vijay Chittoor, CEO Blueshift

Blueshift’s patented method builds an “Interaction Graph” from the event data along with historical customer data and the brand’s catalog of products or content, and uses the graph for continuously computing various forms of AI-Based predictions and recommendations (“personalized merchandising schemes”) continuously. The patented technology also integrates these predictions into customer experiences on channels like email, direct mail, SMS, websites or mobile app notifications, enabling brands to seamlessly use the power of artificial intelligence to deliver 1:1 personalized experiences.

In order to meet today’s marketing and customer challenges, AI must be at the core. With customer data exploding across all channels, customers demanding personalization, and organizations stretched for resources – there is no doubt that brands need AI to organize and execute on the mountains of data to deliver a rich customer experience.

Blueshift’s patented technology was built from the ground up with flexible data models, modern architecture to handle real-time and historic events, continuous learning, and seamless integration with cross-channel automation to deliver the flexibility, adaptability, and control that modern marketers need today to stay competitive.

See more on how Blueshift activates customer data with innovative Interaction Graph technology that continuously learns with customer behavior, and why built-in AI is a must-have for marketers.

Contact Us to put the power of patented AI-powered marketing to work for you.


Born from AI

5 reasons why today’s marketers need built-in AI

Artificial Intelligence is a hot trend today. From Alexa to chat bots, to robots and self driving cars, AI is touching our everyday lives. Companies like Google (AI first), Amazon (Echo) and Apple (Facial Recognition) brought industry attention to Artificial Intelligence at a large scale. Unfortunately, many still think of AI as just a trend, full of hype and little substance. The reality shows real benefits and proves AI is more than just hype.  AI empowers marketers and organizations to deliver individualized experiences in real time and at a scale previously not possible.

Today’s modern marketing and customer data platforms must be architected from the ground up with built-in AI to best perform customer data collection and unification, scalable personalization, predictive analysis, and up-to-the-moment automation.

Let’s look at why “built-in” AI is important.


But first, why is now the time for AI at all?

Artificial Intelligence has been around for a while. Why this sudden rise in attention, particularly in marketing? Today’s customers are connected, and leave a trail of fast changing data in large volumes that is humanly impossible to analyze and use by a marketer. AI is the only way to  crunch through large amounts of data at blazing speeds to understand customers in real-time and eliminate the guesswork.


AI when done right empowers marketers…
  • Get a 360 degree view of customers
  • Deliver 1:1 personalization
  • Segment customers on real time behavior
  • Recommend relevant products/content
  • Predict high value segments
  • Auto-optimize campaigns

While companies are scrambling to add intelligence to existing products by rapidly hiring data science teams or frantically acquiring AI to add on their legacy products, platforms need to be built from the ground up with built-in AI to solve today’s challenges.


The Benefits of Built-in AI

Marketers need full control and flexibility within the platform that learns and adapt with today’s customers. Here are some reasons how built-in AI enables marketers to meet today’s demands.

1. Handle any data from any source, and add new types anytime

Today’s data comes in from different sources (structured like email clicks or unstructured like social behavior) and new types of data keep popping up every day. Marketers need the flexibility to handle any data from any source, and incorporate new sources easily. AI is as good as the data it handles. Platforms with AI should be built with robust data handling capability with flexible data models to collect and process full customer data including attributes and behavior from different sources. Plus, they must accept new data types anytime without the need to re-model.

For example, in the case of a travel site that offers travel to certain cities, they should process user behavior from all channels, and add new behaviors easily. If the organization decides to expand their catalog by adding room+travel packages in the future, marketers should easily be able to add it to the system without remodeling their data, or pulling in any engineering resources.

2. Provide real-time actionable intelligence and, long-term intent and affinities

Marketers can delight customers with 1:1 personalization and predictive recommendations only when they get intelligence on up-to-the moment behavior and long term predictive insights. AI solutions based on modern architectures provide the ability to handle massive amounts of data with both batch and real-time processing within the single framework with no latency.

In the example of the travel site, with AI built on modern architectures, a marketer can send personalized notifications with an upsell offer in real time to a user that just booked on their site. In addition, they can also send promotional offers for travel to a particular city based on that user’s inferred affinities towards certain cities. This kind of a system makes it easy for marketers to make real-time decisions and set up campaigns without depending on other resources.

3. Deeply integrate with product and workflows, so marketers get convenience and control

Marketers are busy. They are under pressure to deliver more with less at a faster rate. Getting slowed down by waiting for other resources is not an option for today’s marketers. AI should be a seamless part of the product with intelligence embedded into the automation functionality, so marketers have both power and convenience. Like a FB designer said, if you don’t notice the AI, you are doing it right.

4. Continuously learn with every customer interaction, without a data science team

A truly intelligent system can learn on its own, getting smarter and enhancing its capabilities with every interaction. Without this, marketers will be restricted to predicting future only on a set of past behaviors. Models should be enriched with every customer behavior in real time, so marketers get up-to-date and relevant actionable intelligence –  without depending on a team of data scientists. For example, the travel site should provide recommendations based on up-to-the-moment behavior of a user and real-time reviews from all their users.

5. Configurable and transparent, so marketers can fine tune to specific needs

Marketers are always looking to improve ROI. With limited budgets and growing competition, they need to maximize the value of every marketing dollar. Predictive models give them the ability to focus on segments and activities that bring the most bang for the buck. Transparency in models provides marketers the trust to make the right decisions. Most importantly, configurability equips marketers to meet their specific business goals.

Today’s marketers obviously need AI to process the massively growing customer data and deliver real time personalized experiences. AI at the core of their platform provides them the flexibility, adaptability, continuous learning and full control to meet the demands of today’s customers.

Friday Five

Friday Five on AI – @Pichai on #AIFirst, #AIMyths, #CX, #DigitalTransformation

Welcome to our Friday Five hot topics on AI from this week. Think of this as that TL;DR of those stories you meant to read or might have missed.

Sundar Pichai says the future of Google is AI. But can he fix the algoritm?

‘One of the most exciting thing we all can do is demystify machine learning and AI’ – Sundar Pichai

Most executives talk about AI like it’s just another thing that’s included in the box or in its cloud; But Pichai is intent on pressing Google’s advantage in AI — by making products that are themselves inspired by AI.

We at Blueshift resonate with Pichai in being inspired by AI and not making it just a check box More on Google’s vision for AI.

5 Myths About Artificial Intelligence (AI) You Must Stop Believing

Something that particularly caught my attention, and hits the nail on its head is Myth#4.

Myth #4: Artificial intelligence will quickly overtake and outpace human intelligence

In some, for example speed of calculations or capacity for recall computers already far outpace us, while in others, such as creative ability, emotional intelligence (such as empathy) and strategic thinking, they are still nowhere near and aren’t likely to be any time soon.

In fact AI should be used as a tool to simplify complex tasks, so humans can focus on creativity and strategic thinking. Isn’t that what marketers and product teams are best at? Check out your other myths about AI in this Forbes article.

How these 5 technologies are improving the customer experience journey

A customer is one of the most crucial aspects of a business enterprise.

Bingo! Chatbots, Big data analytics, AI, Virtual Reality and ioT are transforming every domain in the customer experience. Several businesses are seeing results from their investments. Are you poised to leverage these technologies? Read more on how these technologies can enhance customer experience

How Will Digital Transformation Change the Marketing Funnel?

Digital transformation has changed the roles in the funnel. In fact, I would argue that we are moving away from a funnel based marketing to a customer journey based marketing, especially in B2C.

80% of revenue comes from 20 percent of the prospects, and 80 percent of the pipeline comes from 20% of the campaigns. Predictive analysis like AI identifies the 20 percent.

Technology has introduced new kinds of marketing tools that take the guesswork and grunt work out of marketing. See how AI is transforming and personalizing experiences for customers at different stages.

AI set to dominate agenda at Money20/20

And finally, we were in the news this week. Here’s an in-depth interview with our CEO, Vijay Chittoor on how Blueshift was built with AI at its core to solve marketer’s challenges:

For banks looking to differentiate themselves, providing good customer experience is essential — but not always easy. Retail banking is on the cusp of an artificial intelligence (AI)-driven revolution.

Curious to see more from Money 20/20 happening at the end of this month in Europe as they are devoting a significant time for AI on the agenda.