Forbes .com promoting the benefits of AI bots as a key lever for AI revolutionising marketing….ask us how our platform can work for you…

Artificial Intelligence and digital marketing are beginning to go hand in hand. With the ability to collect data, analyze it, apply it and then learn from it- AI is transforming digital strategy. As it continues to advance, so will the capabilities to use it to improve digital marketing strategies and valuable customer insights for companies.

Here are 3 ways AI is changing digital marketing for the better.

Better User Experience

The most important aspect of a successful digital marketing strategy is great customer experience. When the content is relevant to the user, they are more likely to convert and become recurring customers and have brand loyalty. Artificial intelligence can significantly help with that in its ability to collect data and decide which content is the most applicable based on things like location, historical data and past behavior. When doing so, it gives the user the impression that the brand was built specifically for them.

For retail, AI can be a game changer for online shopping experiences with new advancements in augmented reality where customers can actually “try” a product before making a purchase. There are now apps where you can actually “try on” clothes to see how items will look on you without ever stepping foot into the store. This means less dissatisfied customers, lower returns and higher engagement online for a brand.

Voice search technology is also a great addition of AI in digital marketing that can get faster results. Companies can now write their site to coincide with virtual assistants like Alexa, Google Home and SIRI. If you do it correctly, you can move your brand to be the first result on a voice search which can really help with brand recognition.

Predictive Customer Behavior

Not only can AI personalize a customer experience on past behavior, but it can also predict behavior for new and existing users. With the help of data management platforms (DMP) collecting second and third-party data now, AI can collect information about your users across the internet and not just in a session on your site. This can help personalize to their needs automatically through journeys and profiles enabling you to target your potential leads and eliminating those unlikely to convert enabling you to concentrate on formulating and executing effective marketing strategies.

While it is far from perfect, AI is constantly collecting, analyzing and interpreting data to get smarter at utilizing it. With new algorithms, all the time, accuracy of customer journeys will get more efficient and help determine sales forecasting and ROI so that your business can provide the best experience for customers and right tools to help your business succeed.

Real-time customer support

One of the biggest things customers look for in a good digital experience is quick resolutions and response. With the introduction of AI chatbots, an automated tool that gives the impression of talking to an actual customer service person in real time, AI can deliver that experience in real time.

Chatbots can use terms to seem more “human-like” and can answer basic questions, track and fulfil orders and help solve simple issues. Facebook messenger has integrated the chatbot feature for company Facebook pages to help improve customer service for businesses. These bots can be available 24/7 and can reduce call wait time for customers having issues which can increase customer satisfaction overall.

Artificial intelligence continues to grow and improve and won’t slow down for a while. Implementing AI into your digital marketing strategy will help customers have a better experience and give your business the insights it needs to succeed.

Artificial intelligence continues to grow and improve and won’t slow down for a while. Implementing AI into your digital marketing strategy will help customers have a better experience and give your business the insights it needs to succeed.

Source –


AI marketing can drive customer loyalty to brands, finds survey

AI marketing can drive customer loyalty to brands, finds survey

AI marketing is needed; a survey reveals that poorly targeted marketing material is causing irreparable, long-term damage to thousands of brand-customer relationships.

AI marketing can drive customer loyalty to brands, finds survey image

A new survey has found that 41% of consumers will shun brands that send irrelevant messages and offers. AI marketing may be the answer, however, as the survey also finds that 47% state they are happy for intelligent technology to improve the offers they receive.

The survey was carried out by AI marketing outfit Emarsys, which questioned 2000 UK consumers.

A mere 6% of consumers believe the product and service offers they receive are specifically relevant to them.

The survey also found that:

  • 41% swear they won’t purchase from a brand again if they receive haphazard marketing materials;
  • Over 60% demand that offers they receive be tailored to them and their interests precisely;
  • 66% admitted they would ignore all future marketing from a brand if it sent them hit-or-miss offers.

It is not all bad; opportunity lurks too. The survey also found:

  • 57% admitted they would be more likely to repeat purchase if they received more loyalty-based discounts from a retailer;
  • 41% would be more likely to buy from a brand again if they received bespoke offers which were truly personalised and unique to them.

Emarsys says that: “The problem that most brands encounter though is that human-driven personalisation just doesn’t scale — Segmentation and personalisation designed and executed by marketers doesn’t provide the level of individualisation, at volume, that consumers demand.”

This article was originally posted on Information Age:


IBM Showcases Artificial Intelligence Superiority with Project Debater

The IBM algorithm Deep Blue beat chess champion Garry Kasparov in 1997. It was 2011 when IBM’s Watson won the game show Jeopardy. Shortly after, the IBM Research team was ready to go beyond game playing and began to brainstorm the next feat to challenge an artificial intelligence algorithm. They decided to create an AI algorithm that would be trained on the art of debate.


This past June, a small group of viewers got to see the IBM Project Debater’s public debut and its first two debates, when it went head-to-head with Israeli debaters Dan Zafrir and Noa Ovadia on increased investment in telemedicine and government subsidies for space exploration respectively. From all accounts, IBM Project Debater was a formidable opponent and surprised many with its ability to make human-like arguments. It even swayed more audience members to its position on telemedicine that Zafrir did.

This project was the latest in IBM Research’s goal to build a system “that helps people make evidence-based decisions when answers aren’t black-and-white.”  Debate not only helps us convince others of our opinion, but it can help us understand and learn from other’s views. By training machines in this way, it is hoped that in the future, AI algorithms will be able to help humans make important decisions regularly. IBM Project Debater doesn’t just search its database of millions of articles from well-known newspapers and magazines—its corpus—but it has AI technology that can “work with humans to discover, reason and present new points of view.”

The IBM Research team was able to create an algorithm with the ability to:

  • Generate an opinion driven by data
  • Listen and understand an opponent, parsing out the critical bits of data from flowing narrative
  • Express the situation and arguments with concise language and complete human-like sentences

Even though there were visible stumbling blocks in IBM Project Debater’s debating skills, for the most part, its debut was a resounding success. Since it’s gone from theory to actual implementation, albeit with some tweaks still necessary, it makes you wonder what’s next.


Avoid blind trust by implementing checks and balances

It might be easy for many people to put too much faith in a machine. Although a machine can cull through the data at a rate and depth impossible for humans in a similar timeframe, it’s not immune to bias in its findings. The machine is only as good as the information it was fed. If some of the resources it used to develop its argument contained false logic, the algorithm was influenced by that logic in its debate. Being able to search and summarize millions of human-generated articles is no small feat, but Project Debater’s prowess isn’t representative—yet—of some superintelligence capable of reasoning in a self-generated manner (although that’s likely on the horizon).

To avoid machines just echoing back erroneous human opinions—or being manipulated by a government or corporation for its own purposes—there needs to be a system of checks and balances to ensure the program’s credibility.

IBM’s Project Debater work critical to natural language processing advances

Natural language processing is progressing on many fronts; however, what Project Debater exhibited was progress in loosely structured language in the form of conversations and articles. An algorithm’s ability to put together an argument based on small pieces of text supported by facts while understanding all the facets of an argument (logical, emotional) is a higher level function.  Project Debater can analyze its opponent’s argument and determine the appropriate response supported by facts. This represents a massive leap from “present information” to “make an argument.”

Practical applications of this technology

One of the impressive abilities IBM Project Debater exhibited was the combination of AI techniques it relied upon to solve many problems and join them together in a solution. Now that IBM Research succeeded in this first debate, the team needs to determine practical applications of this technology that they can sell. That’s precisely what Arvind Krishna, Director of IBM Research said he plans to do: “Project Debater’s underlying technologies will also be commercialized in IBM Cloud and IBM Watson in the future.”

Now that AI has gone beyond playing games to learning the art of persuasion and debate; it has proven that it can handle the “gray area” and nuances of human interaction and not just follow clear-cut rules.

“From our perspective, the debate format is the means and not the end. It’s a way to push the technology forward and part of our bigger strategy of mastering language,” said Aya Soffer, who runs IBM Research’s global AI team.

It was an impressive debut, and it will be intriguing to see what’s up next.


This article was originally posted on Forbes

From automation to opacity: Overcoming marketers’ AI anxieties

Artificial intelligence is revolutionizing businesses across industries. More than half of the executives surveyed in a 2017 PwC report said that AI solutions were already increasing their companies’ productivity. As usual, marketers are at the forefront, embracing AI at a particularly rapid pace.

But while any new resource can create excitement in some, it can make others feel uncertain—sometimes even worried about their futures. Many marketers fear that onboarding AI will fundamentally change the way they do business, and not completely for the better.

Below, we’ll take a cool-headed, logical look at how an AI-powered industry is an opportunity for all. We’ll dive into each area by exploring the misperceptions at the heart of these anxieties through the anonymous confessions of several marketers.

Marketers’ jobs have become more and more unwieldy. Their customers are spread across a growing array of devices and channels. It can be tough—and monumentally time-consuming—to try and make sense of all that data. AI tools are designed to cut through the muck, swiftly organizing information and surfacing insights into customer behavior.

The real problem is that so many humans are expected to function like computers. Today’s marketers are asked to comb through oceans of data, assembling it into something structured and coherent.

AI’s job is to take on that extra workload and free up marketers’ time to do higher-level thinking—what they do best. AI isn’t going to make marketers’ jobs obsolete; it will make certain aspects of their jobs manageable for the first time.

It’s true that AI can eliminate mountains of rote, mindless tasks. For example, the Associated Press used AI automation tools to speed up the arduous task of filling out earnings reports. That allowed its staffers to invest that time in telling stories instead. That value is anything but “limited.”

But AI can do much more, augmenting our work by making new connections that give us an edge. For instance, AI tools can comb through social media conversations at breakneck speeds, then take that analysis to the next level by closely analyzing tone and sentiment.

AI can provide invaluable insights that inform our decisions; all we’ll have to do is apply those insights to our creative and strategic decisions. And AI lets us do that in real time.


This article was Originally posted on – Digiday

Chatbot Market: Key Companies Strive to Enhance Customer Experience to Expand User Base

Chatbot Market

The global chatbot market is extremely consolidated with leading three companies namely Facebook, Google, and Microsoft that collectively held a stupendous 97.5% of the market in 2015, states Transparency Market Research in a new report. Being well-established and recognized, these three companies enjoy brand name and most consumers prefer their products and services.

Yahoo Inc. is another significant player in the chatbot market that is popular among users. Howbeit, the massive volume of communication handled by messaging applications such as WeChat, WhatsApp, Line, Skype, Facebook, Twitter, and Kik leaves very little scope for the entry of new players. Competition in the market is stiff as players vie to outdo rivals by delivering better customer experience. They are striving to offer outstanding customer service to resolve customer complaints and issues which will help them steal a march over their competitors.

As per estimates of a report by Transparency Market Research, the global chatbot market will rise at a staggering 27.8% CAGR in terms of revenue over the forecast period between 2016 and 2024. Progressing at this rate, the market will become worth US$994.5 mn in 2024 from US$113.0 mn in 2015. In terms of enterprise size, large enterprises is anticipated to continue to remain key segment and generate a revenue of US$626.3 mn by 2024 end. This is because large enterprises extensively employ chatbot for digital marketing applications and also present a massive demand for chatbot to initiate business process automation activities.

Geography-wise, North America holds a massive share in the overall market; the region is anticipated to hold on to the leading spot over the report’s forecast period.

Use of Chatbots in Digital Marketing Activities Drives Growth

The primary factor boosting the growth of the chatbot market is vast development in artificial intelligence (AI), because of which chatbots have evolved from simple answer machines to a smart platform for engaging consumers. Businesses are also using chatbots for marketing needs that demonstrate the large spectrum capabilities and capacities of chatbots.

Apart from this, technological advancements leading to the implementation of artificial intelligence in consumer electronics is aiding the chatbot market to expand its consumer base. Over the past few years, voice and messaging services have become key and are likely to remain so over the forthcoming years. Businesses are increasingly adopting online messaging services and using chatbots for digital marketing campaigns for customer engagement and for lead generation. This is positively influencing the global chatbots market.

Lack of Application Areas Hurting Growth Prospects

The key factor challenging the growth of this market is the significant rise in the capabilities of chatbots which far exceeds the growth in the areas where they can be applied. Further, the growth of this market is restrained due to several hosting issues that need to be resolved. These include chatbot monitoring, management, security, and integration. The failure of hosting services to provide aforementioned services is restraining several enterprises to enjoy the benefits of chatbot. Nevertheless, chatbot as a service is likely to provide significant opportunities to the market in the forthcoming years.


This article was originally posted on cmfenews –

Chatbot Market: Key Companies Strive to Enhance Customer Experience to Expand User Base




How Marketers Can Start Integrating AI in Their Work



According to Constellation Research, businesses across all sectors will spend more than $100 billion per year on Artificial Intelligence (AI) technologies by 2025, up from a mere $2 billion in 2015. The marketing industry will be no exception.

AI holds great promise for making marketing more intelligent, efficient, consumer-friendly, and, ultimately, more effective. Perhaps more pointedly, though, AI will soon move from being a “nice-to-have” capability to a “have-to-have.” AI is simply a requirement for making sense of the vast arrays of data — both structured and unstructured — being generated from an explosion of digital touchpoints to extract actionable insights at speeds no human could ever replicate in order to deliver the personalized service consumers now demand.

Interestingly, in many cases, the sophistication of AI technologies has already advanced further and faster than most marketers’ ability to actually make use of them. On the one hand, there are the technical challenges of gathering and normalizing data inputs — the act of making different types of data comparable — connecting them to a unified view of the customer, and then aligning the AI-driven decisions to real-world actions. On the other hand, there are also real philosophical, ethical, or at least policydecisions to be made on the value exchange between marketers and consumers when data is shared and used to optimize marketing experiences.

The good news is that, as an industry, we are starting to see meaningful progress on both fronts. For businesses looking to keep pace with innovation and leverage AI, there are steps they can take today. But first, what are some examples of how AI can help make marketing more effective?

Using AI in Marketing

Smart marketers are developing, partnering to build, or integrating AI into their tech stacks to get better at what they do. AI is already being used in ad targeting and customer segmentation, but there are more possibilities in store such as:

  • AI-powered chatbots use all the customer data at their disposal to answer questions and give advice to customers considering making a purchase. Take Sephora’s Kik bot, which quizzes customers about their makeup preferences and then follows up with specific product information.
  • AI-enhanced image search allows users to upload pictures of products they are interested in, to find relevant shopping ideas. For example, companies such as CamFind let you snap a picture of something in the physical world, and get information related to it. Say you see a poster for a movie you’d like to see.  Snap a photo, and CamFind will show you movie recommendations, times, and locations.
  • Personalized training routines and nutrition information can be created based on data from other consumers with similar lifestyles. For example, UnderArmour leveraged IBM Watson’s AI to create a “personal health consultant” that provides users with timely, evidence-based coaching around sleep, fitness, activity, and nutrition.
  • Optimized advertising uses AI to make decisions based on the full range of data available — including unstructured data such as sentiment and mood. For example, IBM, this time as a corporate marketer, teamed up with MediaMath (where I am the CMO/CSO) to activate true AI-driven programmatic marketing using its Watson Cognitive Bidder, to extract predictive signals from exposure to large amounts of data.

How to Put AI Into Practice

There are three key areas of consideration to help you get started leveraging AI for marketing today: affirm your consumer data policies, make your data actionable, and select the right AI partner.  Let’s look at each in more detail:

Affirm your consumer data policies: Before getting started, it is important to confirm your policies regarding the handling of consumer data, transparency, and control.  Your company needs to make sure that you’re complying with the EU’s new General Data Protection Regulation (GDPR). Consumers should be able to interact with connected devices — from web browsers to mobile phones to voice assistants — knowing that their data is being used in transparent ways, in a manner consistent with their preferences and expectations, to which they have explicitly consented.

Make your data actionable: There are three pillars here to consider:

  1. Common identifier: With the explosion of devices, digital identity today is deeply fragmented, leading to head-scratching experiences where, for example, a gym franchise might roll out a great new membership offer…to someone who is already a member. The first step is to establish a common identifier, usually an alpha-numeric string, across various touch points and data sets to help create a unified view of the customer. Emerging solutions such as DigiTrust are helping marketers tie together their various touchpoints in a safe, respectful, and scalable way.
  2. Data gathering: AI can make sense of all your data and extract insights from it, but only if you can collect and normalize it before activating it. Choose a data management platform (DMP) that incorporates the identity solution selected above and can handle data from a wide range of sources, so you can collect, organize, and centrally manage all your data, segment it into granular audiences, and activate it for marketing in real-time.
  3. Data end points: The best customer experiences cut across touchpoints, whether they are “paid” (online, Connected TV, or digital audio ads), “owned” (your stores, websites, call centers) or “earned” (PR, blog posts, social media). Although there are as yet few platforms that can deliver marketing across all of these touchpoints, technology such as IBM’s cloud-based Universal Business Exchange can build upon the common identifier and data gathered to drive consistent execution across a range of platforms and tools.

 Select the right AI partner: With the policies, data assets, and pipes in place, the stage is set for AI to make optimal decisions and drive real business performance. For best results and fastest time to real return on your investment, be sure to choose a partner that has true AI, not simply rules-based decisioning, which is impossible to scale for the volume of data and combinations of interactions that marketers are managing today. In addition, be sure to choose partners with real experience addressing your particular use cases and working with your existing technology partners. Finally, as with any vendor relationship, be sure to check on your partner’s ethical and philosophical approach to AI, as this is still an emerging technology that demands thoughtful guardrails to produce effective results in a responsible manner.

AI is no longer just hype — it’s a “have to have” that you can start integrating into your marketing today with the steps outlined above.

This article was originally posted on –

About The Author

Dan Rosenberg is CMO/CSO at MediaMath.