Cycle du hype de Gartner: L’IA, propulsée entre les mains de tous

Dans 10 ans, l’intelligence artificielle sera partout, et plus seulement entre les mains des professionnels, d’après Gartner. La démocratisation de l’IA est en effet l’une des cinq principales prédictions technologiques identifiées par l’entreprise de recherche et de conseil dans l’édition 2018 de sa fameuse courbe du « Cycle du hype ». Cette courbe montre les technologies émergentes et identifie leur position sur le cycle du hype.

Réalisé à partir de l’analyse de 2 000 technologies réparties ensuite en 35 domaines émergents, le rapport identifie cette année en particulier cinq tendances technologiques qui vont brouiller les frontières entre les humains et les machines.

Crédit: Gartner (août 2018)

L’IA, propulsée entre les mains de tous

En ce qui concerne l’intelligence artificielle, «les technologies d’IA seront pratiquement partout au cours des 10 prochaines années», prédit Gartner. « Ces technologies, qui permettent aux ‘early adopters’ de s’adapter à de nouvelles situations et de résoudre de nouveaux problèmes, vont être mises à la disposition des masses – démocratisées. Des tendances comme le cloud computing, la communauté des ‘makers’ et l’open source vont propulser l’IA entre les mains de tout le monde».

Un futur qui sera rendu possible par les technologies suivantes: l’AI Platform-as a-Service (PaaS)l’Artificial General Intelligence, la conduite autonome, les robots mobiles autonomes, les plateformes conversationnelles basées sur l’IA, les deep neural networks, les véhicules autonomes volants, les robots intelligents et les assistants virtuels.

Les nouvelles opportunités liées aux écosystèmes numérisés

Parmi les quatre autres principales tendances qui vont brouiller les frontières entre les humains et les machines, Gartner a également identifié «les technologies des écosystèmes numérisés qui font leur chemin rapidement vers le Cycle du hype», explique Mike J. Walker, vice-président de la recherche. «Les plateformes de type blockchain et IoT ont désormais atteint leur apogée et nous pensons qu’elles arriveront à maturité dans les cinq à dix prochaines années».

Le rapport prévoit ainsi que le passage d’un modèle technique d’infrastructure compartimenté vers un écosystème de plateformes pose les bases de l’émergence de nouveaux business models qui constitueront «un pont entre l’Homme et la technologie».

Le «do-it-yourself biohacking»

«Au cours de la prochaine décennie, l’humanité commencera son ère ‘transhumaine’: la biologie pourra alors être piratée en fonction du mode de vie, des intérêts et des besoins de santé », explique Gartner. La société sera alors amenée à se demander les applications qu’elle est prête à accepter et à réfléchir aux enjeux éthiques.

Pour le cabinet, cette tendance concerne quatre secteurs d’activité : les technologies d’augmentation, la nutrigénomique, la biologie expérimentale et le « grinder biohacking », mouvement dont les membres souhaitent améliorer leurs capacités physiques grâce à des implants cybernétiques «fait maison».

Les expériences transparentes et immersives pour une vie plus intelligente

L’étude cite également la catégorie des expériences transparentes et immersives. « La technologie continuera à devenir plus centrée sur l’Homme, au point de favoriser la transparence entre les personnes, les entreprises et les choses». Pour Gartner, cela permettra notamment aux hommes de travailler et de vivre de façon plus intelligente. Cette évolution sera possible grâce aux technologies suivantes : l’impression 4D, la maison connectée, le Edge AI, la technologie auto-réparatrice, les batteries d’anodes à base de silicium, la poussière intelligente (Smart Dust), le Smart Workplace et les écrans volumétriques.

L’infrastructure omniprésente

Cinquième et dernière tendance, l’infrastructure omniprésente. Comme l’explique Gartner, «les technologies prenant en charge une infrastructure omniprésente sont en passe d’atteindre le sommet et de progresser rapidement au sein du Cycle du hype. Les circuits intégrés propres à une application (ASIC) 5G et de réseau de neurones profonds, en particulier, devraient atteindre le plateau au cours des deux à cinq prochaines années».

54 Artificial Intelligence Powered Marketing Tools

Lee Odden on Mar 21st, 2018     Digital Marketing

AI Powered Marketing Tools

The expression, “Marketers are data rich and insight poor” is more true today than ever.

Marketers all over the world are working to optimize marketing operations and effectiveness using their abundance of data. Many are turning to tools and platforms powered by artificial intelligence and machine learning. AI promises to make sense of all the dark data companies are sitting on as well as structured and unstructured data online to surface insights about customer behaviors, opportunistic content and emotional triggers to inspire conversions.

In an age of too many choices, increased competition for customer attention requires every advantage to optimize for reach, engagement and conversion. Marketers are using AI to automate and optimize their marketing because that’s what it will take to meet customer appetite for personalized experiences.

  • In a study by Smart Insights, AI and Machine Learning were rated the #3 marketing activity that will make the largest commercial impact on business in 2018.
  • Another study by Salesforce found that high-performing marketing teams are more than 2 times as likely to use AI in their campaigns than under-performers.

What are marketers doing with AI? Areas of focus include advertising automation and optimization, chat bots for service and assisting in sales, and content personalization to name a few.

Chat apps and bots are increasingly being used beyond light customer service to engage customers during the sales process. In fact, 1.82 billion people worldwide are projected to use a chat app in 2018 and by 2020, customers will manage 85% of their relationship with the enterprise without interacting with a human.

Make no mistake, the artificial intelligence platform market is growing fast: it’s estimated to be worth $9.88 billion by 2022.

As Josh Nite mentioned in his recent post, “This changes everything. AI is transforming digital marketing.” From A to Z and then some, here are 54 tools that leverage artificial intelligence and machine learning to make your marketing smarter, more efficient and effective.

Acquisio Turing – A set of 30 high frequency predictive algorithms working together to ingest search marketing campaign data across platforms. Data such as seasonality, times of day, times of week, location, positioning, ad platform, campaign and others enable the platform to self-learn and make smart bid and budget decisions in real-time. @acquisio

Acrolinx – Built on an advanced linguistic analytics engine, this software platform “reads” content and guides writers to make it better. @Acrolinx

Albert – An autonomous platform that uses AI: predictive analytics, machine learning, natural language processing and other proprietary algorithms to execute seamlessly across all channels, paid and non-paid, including email, mobile, social, search and display. @albertaimktg

Atomic Reach – Delivers a deep understanding of what makes your content perform and how to perfect it. @Atomic_Reach

Automat -AI and machine-learning technology that helps brands deliver messaging experiences that are tailor made for each individual consumer and dynamically optimizes conversion for the best results. @automat_inc

Bloomreach – An open and intelligent platform for businesses to build, extend, personalize, analyze, test and optimize their digital experiences across all channels. @bloomreachinc

Boost Linquistics – AI-powered platform for your team to drive revenue by personalizing search and browse experiences at scale and AI to improve site structure, content, and landing pages, maximizing SEO at scale and driving traffic. @boost_ling

CaliberMind – Connects, unlocks, and activates data to help high-growth B2B SaaS organizations to acquire new buyers, grow revenue, and improve the customer experience. @calibermind

CONCURED – Uses AI to analyze people’s behavior towards content at scale in order to prescribe what you should create next to maximize engagement and ROI. @concured

Conversica – AI Sales Assistant helps companies find and secure customers more quickly and efficiently by automatically contacting, engaging, qualifying and following up with leads via natural, multi-channel, two-way conversations. @myconversica

CORTEX – A social media content optimization platform for marketers and agencies to continuously improve post engagement. @meetcortex

Crayon – Market and competitive intelligence tools to track, analyze, and act on everything happening outside of the four walls of your business. @Crayon

Datorama – One Platform for all marketing data, investments, KPIs, and decisions to connect data, report across channels and campaigns, and surface the right insights instantly. @Datorama

Demandbase ABM – A comprehensive set of ABM solutions driven by artificial intelligence: platform, targeting, engagement, conversion. @Demandbase

Drift – A conversational marketing and sales platform (chatbot) that connects your business with the best leads in real-time. Like a virtual assistant for your website, Drift lets you turn any conversation into a conversion. @drift

Emarsys – Understand each contact as an individual customer and execute highly personalized campaigns at scale with AI solutions. @emarsys

FindTheRipple – The AI-driven platform supporting marketers in creating content with impact, finding untapped trends and resonating digital assets for target audiences. @findtheripple

Genie – AI-powered recommendation engine from Grey Jean Technologies that provides accurate predictions of consumer purchase behavior. @getgenie

Google Cloud AI – Build chat bots, do analysis of video, images and text. @gcpcloud

HubSpot – Content Strategy Tool helps marketers discover and validate new content ideas that perform well. @hubspot

IBM Watson – Cognitive marketing platform that provides journey pattern analysis, real-time personalization, marketing insights, weather effects and cognitive tagging. @IBMforMarketing

Idio – Demand Orchestration platform that learns from each interaction to improve engagement and accelerate demand at large B2B enterprises. Automates 1:1 engagement with target accounts, at scale & across all digital channels. @idioplatform

Intellyo – The Creator Engine leverages machine learning and data-driven analytics to automatically tell you which actions to take to build quality into your content. Features include topic research, workflow management, content quality analyzer and customizable service integrations. @intellyo

Invoca – Enables granular campaign attribution to understand why customers are calling, gain real-time intelligence about who’s calling and analyze what’s being said in conversations. @invoca

Jetlore – Artificial intelligence-powered “learning to rank” technology that helps retailers build stronger customer loyalty, higher conversions and increased revenues. @Jetlore

KYNDI – Explainable Artificial Intelligence platform for government, financial services, and healthcare with AI products that analyze massive amounts of data, making organizations and people 100X smarter, 100X faster. @kynditech

Lexalytics – Text Analytics & Survey Analysis with customizable Sentiment Analysis, Categorization & Named Entity Extraction. Platform leverages machine learning, artificial intelligence and natural language processing to allow enterprises to create custom analytics solutions to address their unique data problems. @lexalytics

LiftIgniter – Machine learning personalization recommendation and discovery engine enables every website and app to have a 1:1 “conversation” with users. @liftigniter

Lucy – Solution from Equals 3 powered by Watson. Lucy delivers insightful conclusions, refined segmentation analysis, killer marketing plans, and world-conquering media strategies. @equals3ai

Market Brew – Artificial Intelligence Platform for SEO Teams. @mktbrew

MarketMuse – AI-powered research assistant that accelerates content creation and optimization so you can win in organic search. @MarketMuseCo

Motiva AI – Learns to adapt your messaging to customers automatically and delivers better engagement, at any scale. @MotivaHQ

Nudge – Access new accounts, analyze deal risk, and measure account health – powered by relationship intelligence. @nudgeai

Onespot – Technology platform for personalizing content marketing across digital channels. @onespot

Oribi – Simplifies analytics to enable marketing and product teams to get valuable data without any help from developers. @getoribi

PaveAI – Turns Google Analytics data in actionable insights + reports with our data science AI algorithm. @paveai

Path – An intelligent messaging platform that helps businesses generate more leads, close sales faster, and improve client service. @chat_path

People.ai – Automatically capture all sales activity to drive intelligent sales management and marketing insights. @ppl_ai

Persado – AI generated language that resonates the most with any audience, segment or individual. @persado

Phrasee – Enterprise marketing solution that uses artificial intelligence to generate brand compliant marketing language on a client-to-client basis. @phrasee

Quill by Narrative Science – Powered by Advanced Natural Language Generation, Quill is an intent-driven system that automatically transforms data into Intelligent Narratives at scale, in conversational language anyone can understand. @narrativesci

Rocco – AI powered social media marketing agent that will suggest fresh content that your followers are likely to engage with. @Rocco_Ai

Salesforce Einstein – A layer of artificial intelligence that delivers predictions and recommendations based on your unique business processes and customer data. @salesforce

Sentient Ascend – A patented AI Conversion Optimization solution that mimics biological evolution, enabling it to quickly learn, adapt and react to determine the best performing design from the building blocks you provide. @sentientdai

Smartly – Facebook and Instagram advertising automation and optimization platform with machine learning. @smartlyio

SmartKai – AI-powered assistant that manages your social media marketing. @thesmartkai

Stackla – AI-powered enterprise platform to discover, manage and display the most engaging user generated visual content across all marketing touchpoints. @stackla

The Grid – Molly, a AI-powered web design platform uses machine learning combined with constraint-based design and flow-based programming to make form dynamically adapt to content. @thegrid

Unmetric – Xia provides AI powered social media marketing insights to create compelling content. @unmetric

Vestorly – Vestorly uses artificial intelligence to build personalized touch points with news, blogs, or your own content. @vestorly

Wordsmith – Solution from Automated Insights that uses natural language generation to convert data into content. @ainsights

X.ai – An artificial intelligence personal assistant who schedules meetings for users. @xdotai

Yseop – Artificial intelligence software writes and explains data in six languages using natural language generation. @YseopAI

ZetaHub – Marketing Automation powered by AI. @zetaglobal

There you have it. 50 plus tools that leverage artificial intelligence for marketing. For your convenience, I’ve made a list of all Twitter accounts on this AI Marketing Tools list here, in case you want to follow the category easily.

Whether you’re trying to get more out of existing marketing software like analytics or automate content generation or boost your ability to understand customer behavior for better personalization, there’s a tool or platform for you.

At the same time, very few of these AI powered marketing solutions are “set it and forget it”.  They still need humans for optimal performance. That’s why I like the expression “Augmented Intelligence” as a reflection of how people and technology can work together for more optimized marketing. And when it comes to marketing people, I don’t know any better than the team I get work with at TopRank Marketing.

Is Artificial Intelligence In Marketing Overhyped? (Source: Rupa Ganatra / Forbes)

Shutterstock

A recent survey of more than 300 marketers by Resulticks found that almost half thought artificial intelligence was an overhyped industry buzzword and 40% felt skeptical when they saw or heard the term. The survey also found that 47% of marketers believed AI was more fantasy than reality.

source: https://www.forbes.com/sites/rganatra/2018/03/04/is-artificial-intelligence-in-marketing-overhyped/#1c929b176681

Artificial intelligence has certainly become the buzzword of 2018 as brands and retailers increasingly explore how it will impact their business this year and beyond. Speaking at an event recently hosted by StoryStream on the hype behind AI in marketing, it became apparent that whilst AI is in its infancy today, many brands and retailers are already actively using AI for the likes of content creation, content management, customer insights, personalization and customer acquisition.

Brands including Aston MartinShiseido and Mars are already actively embracing AI experimentation in marketing and some have been at it for some time. Food producer Stonewall Kitchen re-platformed it’s entire ecommerce site with Salesforce Commerce Cloud in 2016, creating an entirely AI-driven on-site experience for their shoppers and have already been reaping the results in areas like cart abandonment and average order values. Stonewall’s Director of Marketing and Direct-to-Consumer Sales, Janine Somers estimates that AI technology has been responsible for about 10% of their year-to-date product revenue.

Berlin-based footwear retailer Shoepassion has seen results from utilizing the personalization technology stack Dynamic Yield in the areas of customer segmentation, optimization, messaging, recommendations and connecting the online and offline data to provide a seamless, personalized and connected customer experience at scale. Whilst beauty Start-up Wunder2 has also been experimenting at speed and recently became the first major cosmetics brand to launch an Amazon Alexa Skill. “As a business, we are fascinated with the rapid integration of AI into peoples’ lives. We think the level of adoption will exceed many peoples’ expectation, and create fluid recommendation experiences using AI technology found in Google Home, Alexa, and the recently launched Apple HomePod – it is something we are absolutely developing already,” says Co-Founder and CEO Michael Malinksy.

The expectation and demands of today’s customer are increasing exponentially, whilst the overflow of content and the rising number of content sources makes it more challenging for marketers to manage their content and publish relevant content across multiple channels. CEO and Co-founder of StoryStream Alex Vaidya says, “today’s customers are ultra-connected, looking for instant gratification and searching for high-quality personalized purchasing experiences from brands.” The UK’s fifth largest retailer Co-op recently used StoryStream’s new AI platform Aura for their #nowcookit campaign across content analytics, digital asset management and multichannel publishing which saw dwell times on their website increase by up to 5x, an 11% conversion rate and an 8x improvement in content curation time for the retailer’s marketing team.

Cosmetics company Shiseido use Salesforce’s Marketing Cloud and Equals 3’s cognitive companion Lucy. Their Chief Digital Officer Alessio Rossi says, “with these platforms, we are building a more complete view of who our customers are by aggregating and analyzing all the data fragments to build customer profiles that are more meaningful and actionable for us.” Whilst the digitally native cosmetics brand Wunder2, famous for having produced the Internet’s most viral brow product, has been utilizing technology from IBM Watson to do analysis on 500,000 Customer FB posts and comments to identify sentiment, allowing them to categorize posts and comments. This has given them large scale data to help understand typical concerns, questions, sources and instances of negativity and build strategies to address and pre-empt them where possible.

With so many choices out there, choosing the best AI platforms for obtaining customer insights and delivering personalization at true scale is key for retailers. As Anoop Vasisht, GM Europe at AI technology platform Dynamic Yield points out, “building online experiences had traditionally been accomplished through a disjointed series of solutions. Retailers would turn to one vendor to serve pop-up messages, another for email personalization and another to provide product recommendations. This not only resulted in data silos but became increasingly difficult to manage so many technologies in the marketing stack and ultimately customer experience took a hit.”

Working with retailers including Sephora Digital SEAOcado and Shoepassion, the Dynamic Yield AI technology stack permits marketers to consistently scale personalization across multiple channels within a single solution. Berlin-based retailer Shoepassion is now able to identify the context of their consumers at scale online via an automated segmentation platform. “If you know that a customer likes to buy a certain type of leather shoe every Winter, you want to be in a position to deliver that content to that customer in their shoe size every time they interact with your brand, across all channels,” says Vasisht. Personalized messaging and product recommendations across web and email are other areas where Shoepassionhas used the Dynamic Yield stack. “If for example it’s a repeat buyer, you may want to show similar products to previous purchases whilst for others, you may want to show the most popular products. Dynamic Yield allows you to personalize for different audiences and optimize the different strategies at scale.”

Stonewall Kitchen has also found success in personalizing their customer relationships through the areas of customer segmentation, email personalization, predictive recommendations and optimizing cart abandonment. Emails shared with their customers and prospects who hadn’t opened one in more than six months had a 9.7% click rate and a 4% conversion rate. Additionally, predictive recommendations resulted in $182,000 in attributable revenue. Somers says, “Salesforce’s AI capabilities have helped solve for many challenges including ’empty cart syndrome,’ providing our shoppers with personalized product recommendations if their cart remains empty for a certain amount of time. Overall, we’ve seen 83% of these suggested products added to a shopper’s cart.”

For many, an AI approach to customer segmentation has also increased the number of segments that they look at. For example, AI has helped Magic Day’s owner Maksym Podsolonko connect the dots between requests, their proposals and customer feedback. It has also led to increasing the customer segments from 7 to 61, whilst only focusing on targeting 4 of them. This level of segmentation and precise targeting has helped them increase revenue with minimal resources making his business ultimately more efficient.

In addition to segmenting existing customers, AI technology is also being used to identify new potential customers in new markets by both Aston Martin and Mars. Aston Martin recently used AI technology KanKan to identify potential customers in China. They wanted to understand the difference between a Tesla buyer and other luxury car brands and were able to do this by aggregating data from both social and retail behavior.

Mars Wrigley Confectionary has been using a reply-based social advertising tool on Twitter called Respondology for their goodnessKNOWS brand to offer product incentives to new audiences outside their existing fan base. Through the platform, they’ve been able to find and vet target-right consumers and offer them a discount off their online purchases. Whilst they are still in the infancy of leveraging the platform to its fullest capability, they have already seen an increase in online ecommerce sales and consumer engagement from it. “One of the biggest benefits so far for goodnessKNOWS has been that we can accelerate a process that we’ve typically done manually, to ultimately reach more brand-right consumers who are looking for a product like ours. Our Respondology campaign has enabled us to reach target-right consumers with relevant product messaging based on conversations they are already having online. We’ve seen a more engaged social community and a ripple effect of consumers sharing their love for our brand and product,” says Eric Epstein, Marketing Director of Snacks for Mars Wrigley Confectionary.

The potential for turning endless amounts of consumer data into actionable marketing campaigns, provide personalization at scale across multiple channels and drive increasing efficiency within marketing teams are key for brands and retailers competing in today’s hyper-commoditized landscape. As AI experimentation continues in these areas, it will be important for brands and retailers to select the right technology partners, be willing to try out new strategies and ultimately, figure out what does and does not have an impact on their bottom-line, at speed.

The five Ps of AI strategy for marketers (Author: Mark Patron)

Some predict that Artificial Intelligence will drive the next industrial revolution. What is certain is that over the next few years AI will become more important to marketers.

Image associéeSource: https://econsultancy.com/blog/69714-the-five-ps-of-ai-strategy-for-marketers/

But to unlock AI’s huge potential you need an AI strategy. Here are five Ps to help you develop yours.

Purpose

AI for what? How can AI help your organisation? What business problem are you trying to solve?

AI is good at targeting ads, product recommendations, deciding if someone is likely to repay a loan, face and voice recognition, even driving cars. AI is not good at more profound thinking such as creativity and innovation.

The economics of your business can help guide you to areas where AI can add value. Customer acquisition, conversion and retention are good places to start. Consider the whole customer journey.

Anything that you can automate is a good candidate for AI. Gartner forecasts that by 2020, customers will manage 85% of their relationship with the enterprise without interacting with a human. That will require a lot of automation. AI can help with the necessary personalisation of targeting, content and customer journey. Optimising those three things in real-time is better suited to AI than a human being.

Benchmark your competitors and similar industries for potential AI applications. One of the reasons AI is not more developed is that many organisations are yet to work out what they can do with AI. With AI answers are easy, it’s the questions that tend to be more difficult.

Predictive data

The increasing power of computers and the greater availability of digital data have fuelled the growth of AI.

First ask yourself if you can access the data you need to fulfil what you want to achieve with AI? Ideally you want a single customer view. Data silos can be a challenge. Data integration tools such as tag management and APIs are improving things but we still have a long way to go. Data is often the largest part of an AI project. Two thirds of the work in data mining projects is typically data preparation.

As with all things IT – rubbish in, rubbish out. Data quality is important. Data needs to be predictive. If you have lots of data variables, by the time you add the last variable it is less likely to add much value to the overall AI solution. The answer may have already been found with the previous data. Data gives diminishing returns, especially if it is all saying the same thing. For example, customer databases in the financial services industry normally contain lots of wealth indicators. Ideally you want different types of predictive data.

Sustainable competitive advantage and barriers to entry tend to be data rather than AI related. Data is easier to protect than AI. Data is less easy to copy than an AI algorithm. You do not need to own all the data, just enough to put competitors off from copying you.

People

AI needs people to make it work. Similar to how digital started, develop a centre of excellence. Centralise your AI task team. Then over time integrate AI resources into the business units.

Recruiting and retaining AI people is hard. Good analysts are like gold-dust. You want people who are good with numbers and analysis, communicate well and understand your business. Not an easy combination to find.

Do you use internal or external personnel? It’s often best to pilot AI externally and over time bring proven AI value in-house. External resources may be more flexible and knowledgeable about the many different AI possibilities. Internal resources will work out cheaper and may be better at optimising your AI solutions in the long run.

Process

Building an AI capability is not a short term project. It is a long term process. Changing your organisation’s culture to embrace and leverage AI takes time.

Initially keep it simple. Walk before you run. Start with quick wins to build corporate confidence. Things change so AI algorithms need to be regularly updated. You need an optimisation process to continually improve them.

ROI is obviously important. The incremental improvement AI brings has to outweigh the total costs of implementing AI. That is why testing is vital. AI is ideally suited to digital businesses that have developed an agile, data driven, test and learn culture.

Platform

Last but not least, which AI platform? I say last because the choice of platform should only come after the four Ps above. Don’t rush into the mistake many marketers make of buying the latest technology and then wondering why it has not fixed the problem.

There are many AI platforms available from cloud providers such as Amazon, Microsoft, Google and IBM to many new start-ups. Which of the numerous tools available is best for your organisation will become clear over time. And you do have time. AI is not built in a day. It’s much more important to grow a strong AI capability than finish a few quick and dirty AI projects.

AI is poised to unlock incredible value for marketers. Define your goals, then test and optimise your AI processes. Develop talented people who can capitalise on AI. The next industrial revolution will come when enough smart people start asking the right questions about what AI can do.

These startups use AI to “optimize” marketing messages (Author: AMBER LEIGH TURNER )

These startups use AI to “optimize” marketing messages

Source: https://thenextweb.com/full-stack/2017/12/29/these-startups-use-ai-to-optimize-marketing-messages/

In a world where artificial intelligence (AI) is gaining traction and being applied in a variety of ways, is it really possible for AI to do intuitive things better than humans can, such as marketing messaging? Marketing messaging seems like something that takes human brain power to fully develop, understand, and formulate to optimize return, so could an AI-powered service offer better results?

Several startups are aiming to do just that. They are utilizing AI to help optimize marketing messages and better deliver marketing and email campaigns that help increase open rates, conversion rates, click-through rates, and overall increase the ROI on marketing.

AI-messaging based on the crowd’s preferences

One of those startups harnessing the power of AI is Persado. Persado’s aim is to use AI and machine learning to “optimize” marketing messages, or, in other words, make them better for the receiver. In Persado’s words, they aim for “AI generated language that resonates the most with any audience, segment, or individual.”

Persado runs your current marketing message through its database of millions of different marketing phrases to tweak the phrase to get the best return based on how these marketing phrases yielded the customer behavior desired. The company has executed over 8,800 marketing campaigns and achieved over 100 billion impressions for their customers, including brands like Verizon, Microsoft, Expedia, and Vodafone. This has resulted in over $1 billion in incremental revenue that wouldn’t have otherwise been realized.

While it seems like Persado would work for large companies, they claim it can work for just about any type of company large and small. “Persado Professional helps individual marketers or employees with hassle-free predictive and data-driven message creation capabilities,” states Geeta Bharathi on behalf of Persado.

Persado works in two ways: email and social. It not only can generate “high-performing language for email subject lines with integrations into email marketing platforms such as Bronto and Mailchimp,” but it can also “generate paid ad units for Facebook, including headlines, text overlays, and images that emotionally engage an audience,” details Bharathi.

Add some anxiety to your message

One specific way Persado has worked (that small businesses could utilize for themselves) is call-to-action phrases. According to Bharathi, Persado recently worked with Air Canada and discovered that incorporating a little bit FOMO (fear of missing out) in their messaging drove an email campaign to have 48 percent more opens and 220 percent more click-throughs by changing the call-to-action button text in an email from “book now” to “see deals.”

“Persado’s work gave Air Canada marketers the enhanced ability to examine how their audience would react to different kinds of emotional language and drive better engagement with the brand,” Bharathi explains.

In a way, it seems that Persado wants AI to make things more human and relatable, while us humans are busy making things less human and more technical. The company could make things much easier for SMEs by bringing a more refined and approachable element, “undoing” in a way this mentality that small enterprises have to do what the larger companies do in order to be successful. By taking their best marketing message and optimizing it, it allows small businesses to compete just as well as larger companies.

AI-messaging based on the customer’s preferences

Persado isn’t alone in their endeavors. While they may be trying to scale the ability to create better messaging for all who use their service, Motiva aims at learning about your customers and tailoring messaging to them.

According to David Gutelius, CEO of Motiva, “Motiva AI gives marketing teams superpowers. It’s like having a really smart assistant that can design and execute all your messaging optimization and testing, interpret the results, and put the latest learning back into your campaigns for you.”

One thing that Motiva handles well, adds Gutelius, is offering insight about new customer segments you can target; potential buyers that you may not have even been aware of based on previous results. Motiva then allows you to craft more effective marketing messaging to reach that new segment.

Gutelius further details that it’s not uncommon to see open and click-through rates double when using Motiva, and it isn’t just a one-off benefit—over time Motiva adapts to the results it is getting, making each marketing message more optimize and effective than the last.

He does point out though that Motiva works best for companies who are “driven by a genuine care for customers” that have an attitude toward incremental improvements all the time. If companies are looking just to input so-so messaging into Motiva to make it a diamond in the end, it’s likely not the best fit for them.

What makes Motiva different is that it learns from your customers’ decisions and adapts over time, where Persado creates messaging from a massive database of phrases from various other sources to find the best one.

A very close competitor of Persado is Phrasee. They focus more on email marketing by claiming to write “better subject lines and email copy” than humans can. They also have a few large clients, such as Dominos and Virgin Holidays, and state that Phrasee generally works best with brands grossing $10 million or more a year. This is because often these companies have enough data from which Phrasee can perform optimally.

What makes Phrasee different is that they don’t have a massive database of words and phrases like Persado does. Phrasee “creates localized models on a client-to-client basis that create natural language generation algorithms,” according to Roxy Cameron, digital marketing manager for Phrasee.

Phrasee even backs up their claims with case studies, one of which is Dominos. Their website states that after two months of using Phrasee, they increased their open email rate by 26%, their clicks by 57 percent, and had a 753 percent ROI.

End of the copywriter?

With Persado, Motiva, and Phrasee, where does that leave copywriters and advertisers in this new world of AI-optimized marketing messaging? Copywriters would still be needed to create the best marketing message that would initially be sent in to be optimized, as these AI-driven marketing messaging services need something good to start with. Once a message comes back “optimized,” it’s still up to a marketer or copywriter to make sure the message is as intended and still fits well with their marketing goals.

For advertisers, using AI to optimize their marketing messaging allows a competitive advantage that their competition may not be able to tap into. Being first out the gate with better marketing messaging may attract better and longer lasting attention, even if a competitor were to step in and use Persado or others in their messaging later on. It would allow advertisers to also better plan their marketing campaigns and hit their goals better should AII optimize marketing messages just right for their companies.

As for if Persado, Motiva, Phrasee, or the like would replace the likes of copywriters and marketing departments, that’s unlikely in the near future. Using AI to craft better marketing messages would be a huge upgrade to what they are currently doing, but not necessarily replace the humans, as these services require human input first, then human review afterward.

How small businesses can benefit

For small businesses and enterprises, using software by Persado or its competitors could help boost their business. By optimizing their messages and making conversions over time, these companies might even reach the point where they could hire a copywriter or marketer who could then take over and continue using AI optimize messaging and scale it.

The power of AI optimized messaging could open a whole new world for companies struggling to get traction with their marketing messaging, or wish to have better brand engagement and conversions. Does this mean that all of our messaging in the future will be optimized by AI? Only time will tell, but companies like Persado, Motiva, and Phrasee aim to do just that — having every marketing and email message be optimized and perform better than human messaging.

Artificial Intelligence & Marketing: A.I. Is definitively moving the 4P’s (Kotler) to the S.A.V.E. model through a Hyper Personalized Relation with the consumer

In november 2017,  I had the great pleasure to give a lecture with Professor Hugues Bersini about A.I. and Marketing…

Started (officialy) 50 years ago, AI is now present in marketing. We estimate that it will take about 10 years to reach the plateau of productivity. But tests are supposed to start now.

 

4 predictions for conversational AI in 2018

Image Credit: Shutterstock.com / Zapp2Photo

As marketers look into 2018, they see that the conversational AI landscape is primed for increased consumer adoption. In fact, in a recent survey, nine out of 10 people said they prefer messaging directly with a brand. This year, Apple, Facebook, Google, and Amazon all leaned into messaging and conversation. In 2018, the big four will make conversational AI the main gateway to communicate with the customer.

Consumers and brand marketers will see an uptick in the following areas:

A move beyond basic bots

Words like “chatbot,” “AI,” and “machine learning” are certainly trending at the moment. For a brand, embracing emerging trends and breakthrough technologies like chatbots is imperative, but so is aligning new innovations with a strategy that drives the bottom line.

As a recent Forester report noted, “the honeymoon for enterprises naively celebrating the cure-all promises of artificial intelligence (AI) technologies is over.” In 2018, more brands will put in the hard work and utilize chatbots as a powerful way to acquire new customers and personalize the experience for every person throughout the customer journey. Chatbots designed to segment and engage customers throughout the entire conversation will drive higher metrics than bots that fail to do so.

Facebook Messenger’s Customer Chat will become a game-changer for marketers

In November 2017, Facebook Messenger launched Customer Chat, a plugin that lets businesses have Facebook Messenger conversations right on their own website. With the release of Customer Chat, brands can take advantage of their websites and acquire new customers in the growing Messenger platform for free.

Facebook Messenger Customer Chat is an opportunity for marketers because when people leave a website, it allows them to view or continue their conversation with a brand on their phone, using the Messenger app. Messenger launched in 2008 as a no-frills chat functionality but has since matured into an end-to-end communications platform, while acquiring 1.3 billion users along the way. The adoption of website and mobile integration for Messenger has paved the way for Facebook Messenger to continue its current reign as the leading enterprise chat platform.

Apple enters the enterprise

At the company’s most recent Worldwide Developer Conference, Apple gave a sneak peek into Business Chat. Apple touts Business Chat as a “powerful new way for businesses to connect with customers directly from within Messages.” As Apple states on its developer site, “Business Chat connects businesses with their customers to answer questions, schedule appointments, make payments with Apple Pay, and more.”

Apple users will be able to message a business using the Messages app after seeing a call-to-action in Siri, Maps, Safari, and Spotlight.

This decision to bring customers and businesses closer together via one of its core apps mirrors moves by Facebook Messenger. These are not iMessage chatbots, however. Apple’s intent is to facilitate person-to-person interaction through chat. Adding customer service features in iMessage increases the likelihood people will stay inside Apple instead of going to a brand’s website or a Messenger bot.

Instagram chatbots?

Another huge 1:1 for marketers could exist beyond Facebook Messenger, Apple Business Chat, Google Assistant, and Alexa. In 2018, it would be wise for Instagram to roll out a messaging feature. Instagram’s consistent growth and steady introduction of new features have made the photo-and-video-sharing network a force for leading brands. By adding chatbots, Instagram could empower brands to move beyond hearts and into commerce, customer support, and increased consumer engagement.

Jonathan Shriftman is the director of business development at Snaps, a mobile messaging service.

2018 Predictions for AI Powered Marketing

2018-Predictions-for-AI-in-Marketing-Absolutdata

2017 has been a breakout year for Artificial Intelligence (AI). At Absolutdata, we’ve had the opportunity to work with many sales and marketing organizations—and a lot of data. We’ve seen what’s possible when AI is put into action. And it’s impressive.

As a marketer and a career-long early adopter of marketing tech, I’m particularly excited about the marketing applications of AI. We’re going to see a significant impact on how we allocate budgets, prioritize initiatives and set KPIs.

In 2018, AI will become even more accessible to marketing professionals. What can we expect?

In 2018 AI Will Bring…

  • Real Time Behavioral Indicators: AI’s ability to quickly find patterns that we mere mortals miss will shine a new light on behavior-based marketing initiatives. With AI, we can pick up signals in digital footprints as that data is being created. This puts us well beyond simple personalization techniques like re-targeting. We’ll be able to see someone follow (or abandon) a trend, change their preferences, or even transition to a new job or role. We’ll know when they make a purchase that creates a new opportunity for our offerings. In short, we’ll have a very current knowledge of individual customers’ buying preferences and needs, which we can match up with where they are in their buying journey — a powerful advantage for marketers.
  • Dynamic Segmentation: Interest-based segments and broad demographics are weak foundations for marketing campaigns. Individual consumers and B2B buyers constantly shift their buying patterns, roles, and budgets. When it comes to segmentation, AI can be like a laser. It spots emerging segments, groups buyers in unique ways, and finds promising prospects for specific offers. It’s not blinded by biases or pre-conceived ideas. Well-implemented AI can group engaged prospects into categories based on their actions and behaviors, and it can do it in near-real time.
  • Customer Directed Marketing: Customer Directed Marketing will be the single highest-impact movement in 2018. Marketing and engagement paths will increasingly be driven by the customer rather than the marketer. This isn’t by customer choice — it’s by their actions and the use of AI. But how can we follow the customer? When we use AI to predict customer needs based on their current behavior, we’re letting the customer tell us what action to take next; we’re following the lead of their data. Now the power has shifted from the marketer to the customer. Their actions propel the relationship. In turn, we marketers can use this knowledge to develop more compelling and successful offers.
  • Fewer Campaigns, Higher ROI: Spray-and-pray campaigns (still surprisingly common) are going away. Few marketers want to spend budget on someone who will never become a customer. On the flip side, no consumer wants to be blasted with irrelevant offers. In 2018 we all win. AI allows marketers to be more aware and agile, focusing on the most receptive audience at a given time. Although AI might generate more actual offers—even a campaign for a segment of one—each offer will be sent to a limited number of very suitable prospects. Overall, better-quality targeting will give us a sizable drop in irrelevant communications and a much-improved response rate.
  • More Creative Thinking, Less Routine Work: I’ve also done a lot of routine tasks in my marketing career: sliced target audiences, created personas, managed review cycles, integrated sales and marketing automation systems, performed A/B tests, created pivot tables, drafted surveys, etc. With AI, marketers spend less time on mundane tasks and more time being creative. We can now capture segments as they emerge. Our creative side can be inspired by customer behavior or by crowd-sourced interests. A/B testing ‘happens’ through machine learning. Data replaces endless review cycles. (I’ll toast to THAT!) We get better results — and more data about what works. The incoming data spawns innovative ideas for staying ahead of the game, and it highlights new creative trends that we might otherwise miss.
  • Marketing Tech Stack Consolidation: There are thousands of tools now available to marketing professionals. AI will drive the consolidation and (sorry to say) elimination of some of these tools. In their places, we’ll see new categories of high-efficiency marketing tools and solutions. Tech stack spend will start to focus on ensuring that data sources are high quality, especially as real time data will become a key competitive advantage for marketers.
  • Higher Quality Feed into the Sales Pipeline: In B2B marketing, the love-hate relationship with the MQL (marketing qualified lead) will become friendlier. A simple lead score or a single trigger action doesn’t necessarily mean a prospect is ready to talk to a salesperson. Prospects can go from consideration to having budget in a flash — or it may take months. How can we tell when a prospect is ready? With AI, movement along the buying journey is easier to observe. Since AI detects additional parameters and dynamics, it turns the classic lead score into a multi-dimensional indicator. This produces MQLs that are more likely to turn into revenue — a boon for both sales and marketing.
  • The Emergence of New Buying Journeys: In B2B and B2C transactions, buying journeys are the series of actions someone takes before spending their precious dollars. We can make static maps of these journeys to no end, but the truth is that buying journeys are dynamic and numerous. They vary by group, by consumer, and even by transaction. AI can model and recognize a wide variety of buying signals. It can detect repeat buying journeys and identify new ones as they unfold. Marketers will be able to follow these paths, capture new formulas for success, and quickly emulate those formulas for like-minded customers.
  • Better Understanding of When to STOP Marketing: We’ve all been stalked by ads based on last week’s (or last month’s) shopping activity. I bought a car two years ago and I still get frequent online ads from the dealers and brands I was considering. These marketers are wasting their ad budgets and should be investing in finding active buyers or promoting after-market services. AI can detect the patterns produced by inactive buyers, helping marketers focus their budget on revenue generating signals. The flip side of this coin is that there are also loyal consumers who will buy your brand at a premium price, no matter what. AI can spot these as well, and encourage advocacy and loyalty instead of offering deep discounts.

AI has had some less-than-graceful moments in its debut. Some even consider it a bit creepy. But for this consumer, B2B buyer, and marketer, AI will be a big win in 2018 — no matter what side of the campaign I’m on.

Authored by: Sandra Peterson, VP of Marketing at Absolutdata Analytics

Related products and services: AI & Data ScienceNAVIK MarketingAINAVIK AI PlatformMarketing Analytics

AI marketing and the journey through the uncanny valley

Restoring the brand/consumer relationship in the age of aggressive personalization

“Things usually get worse before they get better.”

“It’s always darkest before the dawn.”

Whether it’s the valley of the shadow of death in the 23rd Psalm or the Dangerous Trench on the way to Shell City in the Sponge Bob movie, we’re used to the concept of feeling that things are getting worse, even though we know we’re headed in the right direction.

This experience can be represented by a U-shaped curve, literally forming the shape of a valley between two peaks. In technical terms, the curve represents a nonlinear relationship between two variables. A specific example is the uncanny valley — the hypothesis of the unease, frustration, or even revulsion we feel as something approaches the behavior and appearance of a human without getting all the way there. In this case, the two variables are the humanlike nature of the object and the emotional response to it. This can be experienced with robots and AI assistants, and with 3D animation. Perhaps you know someone who gets illogically angry when Siri or Alexa fails to understand their commands, or maybe you get uncomfortable watching humanoid robots or CGI-animated humans in TV and movies.

Although 78 percent of marketers are adopting or expanding artificial intelligence marketing in 2018, marketers are also uneasy about the uncanny valley. They are concerned that by implementing AI marketing, they will lose control of the customer experience, possibly bewildering or even revolting their customers. While this is a reasonable concern, it could prove to be an unfounded and risky position — because marketers have already forced their customers into the uncanny valley through the use of marketing automation and aggressive personalization. And to quote another truism, when you’re going through hell, keep going. Because you don’t want to stay there.

Your customers are already in the uncanny valley

Could it be true that we’re already subjecting our customers to experiences that create bewilderment and revulsion? You don’t have to have 3D avatars or robots in your customer experience to create these eerie, negative feelings in your customers. The uncanny valley is represented by a sudden decrease in empathy when a human-like being ceases in some way to be human. Here are some specific examples to indicate that your customers may already be in the uncanny valley:

Broken context

Example: An AI assistant or chatbot initially passes for human but fails to understand the context of a question that would be simple for a human to understand, revealing that it is not human. Here is just one of many anecdotes from Reddit:

In just seconds, this user went from loving their Echo to figuratively (literally?) flipping the table in frustration.

Not quite lookalikes

Example: A cursory read of our example user’s Facebook history could tell you that he is a foodie, a vegetarian and a fan of subscription boxes. Recently, this user got targeted by a new artisanal food subscription service that was relevant in many respects, except for the fact that they exclusively offer cured meats. It’s reasonable in some respects that an artisanal cured meat subscription service would target him. Except that as a vegetarian, this user found their ad bewildering and invasive, causing him to lose interest and scroll quickly past. In his scrolling fervor, he accidentally registered a click on the ad, leading to weeks of cured meats in his feed.

Bad timing

Another example from that same user: Currently, his bank is aggressively targeting him with a competitive mortgage offer. Three weeks ago, there were credit, fund consolidation and other signals that he was preparing for a home purchase. At that point, it was stone cold silence from the bank. But now that he has signed a mortgage with another bank and closed escrow, he is getting targeted after the fact with an offer that he would have considered three weeks ago. Now, it’s just aggravating.

Three ways to ascend from the uncanny valley

Ascending from the uncanny valley is possible, but it takes buy-in from executives and a concerted effort by the entire marketing organization. Fortunately, Artificial Intelligence Marketing (AIM) provides a new approach for interacting with customers, allowing for consistent relevant experiences across all channels and continuous optimization at scale. Marketers shouldn’t fear the uncanny valley. They should focus on crossing through to the other side. Here’s how:

1. Keep context: Match your level of sophistication across channels

Ideally, your website, app and chatbot work together to provide integrated, personalized service. Your customers should be able to access the same contextual features whether in the mobile app, at the brick-and-mortar store or when chatting with Alexa. If a user clicks through to your site from a specific offer email, that offer should automatically persist on the website. While your customers often encounter the same creative elements across your app, social, display, email and website, they’re disappointed when experiences are disjointed and out-of-context.

Unfortunately, many brand experiences can only be delivered to users in a single channel due to the inherent limitations of current marketing clouds, making a promise of sophisticated interaction that can’t be delivered in other channels.

2. Reduce uncertainty: Use visual cues to signal behavior and ability

If you do have varying levels of sophistication for some of your communication channels, you can give your customer cues to set appropriate expectations. If you have created a bot or an app with sophisticated abilities, imbue it with human personality. In contrast, a limited chatbot doesn’t need a name, a highly humanized voice or an avatar. And if your mobile app focuses on a subset of features, be clear about what they are in the app name and description.

3. Responsiveness: Reduce the lag between insight and action

If you gain insight about an individual customer, how quickly can you adjust your interactions to be responsively relevant? A human conversation involves both parties responding in real time to conscious and subconscious cues. If your campaigns and audience segments are static, or if your channels are siloed, it can take too long to move at the speed of the customer. However, with AI marketing that has dynamic decisioning at its core, new data and behavioral signals can immediately be acted upon without human intervention. The result is a more responsive customer interaction that adapts as your customer evolves.

To get to the other side

Helping your customers ascend out of the uncanny valley can seem like a monumental task, but with AI marketing, it is now feasible. Consumer brands that make the leap and move away from the rules will be the first to reap the benefits of consistent, cross-channel interactions that are optimized at scale by AI.

ABOUT THE AUTHOR

Amplero is an Artificial Intelligence Marketing (AIM) company that enables enterprise B2C marketers to optimize customer lifetime value at a scale that is not humanly possible. Unlike most approaches which bolt AI onto legacy martech stacks, Amplero’s AIM Platform was built with AI at the core, using machine learning and multi-armed bandit experimentation to dynamically test 1000s of permutations to automatically optimize every customer interaction and maximize customer lifetime value and loyalty. Using Amplero, marketers in telecom, banking, gaming and consumer tech have garnered a 1-3% incremental growth in customer topline revenue and 3-5x lift in retention rates.https://www.amplero.com/

AI for Marketing on the Hype Cycle: A Long Journey to the Plateau? 

Source: AI for Marketing on the Hype Cycle: A Long Journey to the Plateau? | How to be a leader in #service: #servicedesign and #designthinking

Gartner’s 2017 Hype Cycle for Marketing and Advertising is out (subscription required) and, predictably, AI for Marketing has appeared as a new dot making a rapid ascent toward the Peak of Inflated Expectations. I say “rapid” but some may be surprised to see us projecting that it will take more than 10 years for AI in Marketing to reach the Plateau of Productivity. Indeed, the timeframe drew some skepticism and we deliberated on this extensively, as have many organizations and communities.

AI for Marketing on the 2017 Hype Cycle for Marketing and Advertising
AI for Marketing on the 2017 Hype Cycle for Marketing and Advertising

First, let’s be clear about one thing: a long journey to the plateau is not a recommendation to ignore a transformational technology. However, it does raise questions of just what to expect in the nearer term.

Skeptics of a longer timeframe rightly point out the velocity with which digital leaders from Google to Amazon to Baidu and Alibaba are embracing these technologies today, and the impact they’re likely to have on marketing and advertising once they’ve cracked the code on predicting buying behavior and customer satisfaction and acting accordingly.

There’s no point in debating the seriousness of the leading digital companies when it comes to AI. The impact that AI will have on marketing is perhaps more debatable – some breakthrough benefits are already being realized, but – to use some AI jargon here – many problems at the heart of marketing exhibit high enough dimensionality to suggest they’re AI-complete. In other words, human behavior is influenced by a large number of variables which makes it hard to predict unless you’re human. On the other hand, we’ve seen dramatic lifts in conversion rates from AI-enhanced campaigns and the global scale of markets means that even modest improvements in matching people with products could have major effects. Net-net, we do believe AI that will have a transformational on marketing and that some of these transformational effects will be felt in fewer than ten years – in fact, they’re being felt already.

Still, in the words of Paul Saffo, “Never mistake a clear view for a short distance.” The magnitude of a technology’s impact is, if anything, a sign it will take longer than expected to reach some sort of equilibrium. Just look at the Internet. I still vividly recall the collective expectation that many of us held in 1999 that business productivity was just around the corner. The ensuing descent into the Trough of Disillusionment didn’t diminish the Internet’s ultimate impact – it just delayed it. But the delay was significant enough to give a few companies that kept the faith, like Google and Amazon, an insurmountable advantage when Internet at last plateaued, about 10 years later.

Proponents of faster impact point out that AI has already been through a Trough of Disillusionment maybe ten times as long as the Internet – the “AI Winter” that you can trace to the 1980s. By this reckoning, productivity is long overdue. This may be true for a number of domains – such as natural language processing and image recognition – but it’s hardly the case for the kinds of applications we’re considering in AI for Marketing. Before we could start on those we needed massive data collection on the input side, a cloud-based big data machine learning infrastructure, and real-time operations on the output side to accelerate the learning process to the point where we could start to frame the optimization problem in AI. Some of the algorithms may be quite old, but their real-time marketingcontext is certainly new.