L’analyse basée sur l’intelligence artificielle (IA) et l’apprentissage machine sera la tendance dominante de la technologie des données en 2019, selon le top 10 des tendances de Gartner en matière de données et d’analyse. Selon le cabinet d’analystes, cette tendance, à l’origine des futures disruptions sur le marché des données et de l’analyse, jette les bases de l’analyse augmentée des données. Révélée lors du Data & Analytics Summit organisé par Gartner à Sydney le 18 février, l’entreprise de conseil estime que d’ici 2022 la gestion manuelle des données sera réduite de 45 % à mesure que les systèmes acquerront la capacité de s’auto-configurer.
Parallèlement, l’intelligence continue, qui consiste à intégrer l’analyse en temps réel dans les opérations de l’entreprise, arrive en troisième position des tendances les plus importantes. Selon Gartner, plus de la moitié des nouveaux systèmes d’entreprise construits d’ici 2022 utiliseront l’intelligence continue. « L’intelligence continue représente un changement majeur dans le travail des équipes de données et d’analyse », a déclaré Rita Sallam, vice-présidente de Gartner chargée de la recherche. « C’est un grand défi – et une grande opportunité – pour les équipes d’analyse et de BI (business intelligence) de parvenir à aider les entreprises à prendre des décisions plus intelligentes en temps réel en 2019. Ce sera sans doute le nec plus ultra en matière de BI opérationnelle ».
Recommandation mais avec des explications
La quatrième tendance la plus importante concerne l’IA explicable ou eXplainable Artificial Intelligence (XAI). Celle-ci consiste pour les chefs d’entreprise à rendre leurs modèles plus interprétables et plus explicables dans le but de gagner la confiance des parties prenantes. Cependant, selon Gartner, la plupart des modèles d’IA avancés sont des « boîtes noires complexes » qui ne sont pas en mesure d’expliquer pourquoi elles sont parvenues à une recommandation ou à une décision particulière. Parmi les autres grandes tendances, il faut aussi mentionner les banques de données graphiques – qui permettent de suivre les interrelations entre les silos de données – et le data fabric, un système de partage. Mais, prévient Gartner, ce système sera dans un premier temps composé d’une « infrastructure statique », ce qui signifie que les entreprises seront obligées d’en modifier la conception plus tard.
L’usage du traitement du langage naturel (NLP) ou de la voix, ou la génération automatique de requêtes de recherche pourraient également figurer parmi les priorités des entreprises. Gartner prévoit aussi que d’ici 2022, 75 % des nouvelles solutions pour utilisateurs finaux utilisant l’intelligence artificielle et les techniques d’apprentissage machine seront construites avec des solutions commerciales plutôt que délivrées par des plates-formes open source. Dans le même temps, les technologies de la chaîne de blocs et du grand livre distribué, ainsi que les technologies de mémoire persistante joueront également un rôle majeur dans les domaines de l’analyse. « La taille, la complexité, la nature distribuée des données, la vitesse d’action et l’intelligence continue requises par le commerce numérique font que les architectures et les outils rigides et centralisés ne seront plus adaptés », a déclaré Donald Feinberg, vice-président et analyste de Gartner. « La survie de toute entreprise dépendra d’une architecture agile, centrée sur les données, qui pourra répondre au rythme permanent du changement ».
Bottom Line: AI and machine learning are enabling omnichannel strategies to scale by providing insights into the changing needs and preferences of customers, creating customer journeys that scale, delivering consistent experiences.
For any omnichannel strategy to succeed, each customer touchpoint needs to be orchestrated as part of an overarching customer journey. That’s the only way to reduce and eventually eliminate customers’ perceptions of using one channel versus another. What makes omnichannel so challenging to excel at is the need to scale a variety of customer journeys in real-time as customers are also changing.
89% of customers used at least one digital channel to interact with their favorite brands and just 13% found the digital-physical experiences well aligned according to Accenture’s omnichannel study. AI and machine learning are being used to close these gaps with greater intelligence and knowledge. Omnichannel strategists are fine-tuning customer personas, measuring how customer journeys change over time, and more precisely define service strategies using AI and machine learning. Disney, Oasis, REI, Starbucks, Virgin Atlantic, and others excel at delivering omnichannel experiences using AI and machine learning for example.
Omnichannel leaders including Amazon use AI and machine learning to anticipate which customer personas prefer to speak with a live agent versus using self-service for example. McKinsey also found omnichannel customer care expectations fall into the three categories of speed and flexibility, reliability and transparency, and interaction and care. Omnichannel customer journeys designed deliver on each of these three categories excel and scale between automated systems and live agents as the following example from the McKinsey article, How to capture what the customer wantsillustrate:
10 Ways AI & Machine Learning Are Revolutionizing Omnichannel
The following are 10 ways AI & machine learning are revolutionizing omnichannel strategies starting with customer personas, their expectations, and how customer care, IT infrastructure and supply chains need to stay responsive to grow.
- AI and machine learning are enabling brands, retailers and manufacturers to more precisely define customer personas, their buying preferences, and journeys. Leading omnichannel retailers are successfully using AI and machine learning today to personalize customer experiences to the persona level. They’re combining brand, event and product preferences, location data, content viewed, transaction histories and most of all, channel and communication preferences to create precise personas of each of their key customer segments.
- Achieving price optimization by persona is now possible using AI and machine learning, factoring in brand and channel preferences, previous purchase history, and price sensitivity. Brands, retailers, and manufacturers are saying that cloud-based price optimization and management apps are easier to use and more powerful based on rapid advances in AI and machine learning algorithms than ever before. The combination of easier to use, more powerful apps and the need to better manage and optimize omnichannel pricing is fueling rapid innovation in this area. The following example is from Microsoft Azure’s Interactive Pricing Analytics Pre-Configured Solution (PCS). Source: Azure Cortana Interactive Pricing Analytics Pre-Configured Solution.
- Capitalizing on insights gained from AI and machine learning, omnichannel leaders are redesigning IT infrastructure and integration so they can scale customer experiences. Succeeding with omnichannel takes an IT infrastructure capable of flexing quickly in response to change in customers’ preferences while providing scale to grow. Every area of a brand, retailer or manufacturer’s supply chain from their supplier onboarding, quality management and strategic sourcing to yard management, dock scheduling, manufacturing, and fulfillment need to be orchestrated around customers. Leaders include C3 Solutionswho offers a web-based Yard Management System (YMS) and Dock Scheduling System that can integrate with ERP, Supply Chain Management (SCM), Warehouse Management Systems (WMS) and many others via APIs. The following graphic illustrates how omnichannel leaders orchestrate IT infrastructure to achieve greater growth. Source: Cognizant, The 2020 Customer Experience.
- Omnichannel leaders are relying on AI and machine learning to digitize their supply chains, enabling on-time performance, fueling faster revenue growth. For any omnichannel strategy to succeed, supply chains need to be designed to excel at time-to-market and time-to-customer performance at scale. 54% of retailers pursuing omnichannel strategies say that their main goal in digitizing their supply chains was to deliver greater customer experiences. 45% say faster speed to market is their primary goal in digitizing their supply chain by adding in AI and machine learning-driven intelligence. Source: Digitize Today To Future-Proof Tomorrow(PDF, 16 pp., opt-in).
- AI and machine learning algorithms are making it possible to create propensity models by persona, and they are invaluable for predicting which customers will act on a bundling or pricing offer. By definition propensity models rely on predictive analytics including machine learning to predict the probability a given customer will act on a bundling or pricing offer, e-mail campaign or other call-to-action leading to a purchase, upsell or cross-sell. Propensity models have proven to be very effective at increasing customer retention and reducing churn. Every business excelling at omnichannel today rely on propensity models to better predict how customers’ preferences and past behavior will lead to future purchases. The following is a dashboard that shows how propensity models work. Source: customer propensities dashboard is from TIBCO.
- Combining machine learning-based pattern matching with a product-based recommendation engine is leading to the development of mobile-based apps where shoppers can virtually try on garments they’re interested in buying.Machine learning excels at pattern recognition, and AI is well-suited for creating recommendation engines, which are together leading to a new generation of shopping apps where customers can virtually try on any garment. The app learns what shoppers most prefer and also evaluates image quality in real-time, and then recommends either purchase online or in a store. Source: Capgemini, Building The Retail Superstar: How unleashing AI across functions offers a multi-billion dollar opportunity.
- 56% of brands and retailers say that order track-and-traceability strengthened with AI and machine learning is essential to delivering excellent customer experiences. Order tracking across each channel combined with predictions of allocation and out-of-stock conditions using AI and machine learning is reducing operating risks today. AI-driven track-and-trace is invaluable in finding where there are process inefficiencies that slow down time-to-market and time-to-customer. Source: Digitize Today To Future-Proof Tomorrow (PDF, 16 pp., opt-in).
- Gartner predicts that by 2025, customer service organizations who embed AI in their customer engagement center platforms will increase operational efficiencies by 25%, revolutionizing customer care in the process. Customer service is often where omnichannel strategies fail due to lack of real-time contextual data and insight. There’s an abundance of use cases in customer service where AI and machine learning can improve overall omnichannel performance. Amazon has taken the lead on using AI and machine learning to decide when a given customer persona needs to speak with a live agent. Comparable strategies can also be created for improving Intelligent Agents, Virtual Personal Assistants, Chatbot and Natural Language (NLP) performance. There’s also the opportunity to improve knowledge management, content discovery and improve field service routing and support.
- AI and machine learning are improving marketing and selling effectiveness by being able to track purchase decisions back to campaigns by channel and understand why specific personas purchased while others didn’t.Marketing is already analytically driven, and with the rapid advances in AI and machine learning, markets will for the first time be able to isolate why and where their omnichannel strategies are succeeding or failing. By using machine learning to qualify the further customer and prospect lists using relevant data from the web, predictive models including machine learning can better predict ideal customer profiles. Each omnichannel sales lead’s predictive score becomes a better predictor of potential new sales, helping sales prioritize time, sales efforts and selling strategies.
- Predictive content analytics powered by AI and machine learning are improving sales close rates by predicting which content will lead a customer to buy. Analyzing previous prospect and buyer behavior by persona using machine learning provides insights into which content needs to be personalized and presented when to get a sale. Predictive content analytics is proving to be very effective in B2B selling scenarios, and are scaling into consumer products as well.
Louis Columbus is an enterprise software strategist with expertise in analytics, cloud computing, CPQ, Customer Relationship Management (CRM), e-commerce and Enterprise Resource Planning (ERP).
Co-Founder of fishbat Media, LLC., Keynote Speaker, SEO Specialist. Featured in CNBC, Yahoo Finance, plus hundreds of other publications.
As 2019 kicks off, businesses are looking for new competitive advantages and ways to connect with more customers. Digital marketing has no signs of slowing down or stopping, which is why business owners are focused on strengthening their digital marketing efforts for the upcoming year. With that being said, here are five digital marketing trends you can expect to see take shape in 2019.
Social Media Will Get Conversational
Businesses should no longer be viewing social media posts as one-way conversations. Instead, 2019 will see brands using social media to engage with audiences and gauge their wants and needs. Effective social listening and paying attention to conversations about their brand and competitors’ brands will help businesses learn what type of content performs better for their target audience. Additional steps that companies can take to develop a more personal relationship with their customers include:
• Asking and answering consumer questions
• Creating and posting engaging subject matter
• Having a quick response time of 24-48 hours
Continue to have conversations on social media through user posts and comments. And personalize the user experience by utilizing user-generated content that resonates with customers. This can help businesses increase brand awareness, gain consumer trust and strengthen brand loyalty.
Videos Will Be Refined For SEO
SEO helps business owners understand user behavior. Since search engines are constantly updating to make sure user-friendly and engaging sites are being shown to users, businesses need to adapt to the changing algorithms to keep their rankings intact. This is where video comes in.
According to research, “Video is shared 1,200% more than both links and text combined.” Videos are highly engaging and have the chance to reach a larger number of users and develop strong emotional connections with viewers.
This year, I predict that businesses will be focusing more on optimizing video content to improve SEO rankings. Ensure that keywords are added into these three aspects of your video:
• Video title
Keywords for videos will vary depending on your industry. You might want to make the title of your video a question, or the answer to a question that viewers tend to search. Closed captioning can also be added to your video. Include high-volume keywords in your video script so that Google can read what the video entails and rank accordingly. Optimize video content so that it is timely, relevant and engaging. When done right, this can help increase social media engagement, generate solid leads, create a more effective call to action and increase sales.
Businesses should also be focusing on improving their SEO for the sake of getting to know their audience. The more precise your SEO strategy, the closer you can get to your target audience.
Geo-Marketing Will Expand
Businesses have been incorporating geo-marketing into their strategy for a while now. But the need for more precise and accurate results has led to new technologies, such as geo-fencing, to get businesses one step closer to their customers. Geo-fencing has evolved the way location-targeting is done by allowing companies to attract competitors’ clients or create awareness for their own brand. One way to take advantage of geo-marketing is to focus on areas that have a heavy saturation of your target market.
Serving digital ads to mobile users within a predefined geographic area is another way to capitalize on geo-marketing. For example, businesses can create and launch a geo-mapping ad a quarter-mile radius from a competitor’s store. Every time a customer walks into that targeted location, they will be served with an ad for your business, potentially sparking interest in your store and brand. These targeted notifications are a great way to produce high engagement and brand awareness for your business.
Email Marketing Will Get Personal
Consumers are more concerned with personalization now than ever before. When it comes to connecting with brands, consumers realize that it’s the little things that matter. Which is why taking the extra step to personalize emails can result in more loyal customers and more conversions. When creating a personalized email marking campaign, be sure to:
• Create specific emails based on your different market segments
• Choose to promote products and services that are interesting for those customers
• Craft short but memorable and impactful content
• Curate creative that is engaging and represents your brand
Not only will emails become more personal, but more businesses are going to focus on making emails more accessible to mobile devices. According to research, nearly 84% of survey respondents said they use their smartphones as their preferred device for personal email.
Making sure your email content is personalized and optimized is extremely important for generating leads and capitalizing on this highly mobile market.
New Technologies Will Rise
During the new year, I believe businesses will begin to integrate new technologies to improve their marketing efforts and enhance their customer experience. Artificial intelligence and augmented reality are two technologies expected to improve a business’s customer service and marketing strategies as a whole.
In order to stay on top of the technology game, be sure to dedicate a certain amount of time each week to become familiar with and understand what’s happening in the digital landscape. When new opportunities like ad platforms or social listening tools arise, it’s important that you are aware of their abilities. One way to stay up to date and ahead of your competitors is to subscribe to RSS feeds and Facebook Pages of information websites. These sources will keep up with new technology and announce the latest and greatest trends available to assist you in your overall marketing objectives.
As companies move into the heart of 2019, it is crucial to keep in mind that implementing one of these trends is good, but incorporating all them cohesively across digital initiatives will lead to even greater results.
Department for Education
I love work that has substance, craft and demonstrably works – real campaigns that solve real client problems. This example is a good old-fashioned advertising solution to a big scary client problem: we need a lot more teachers. A pretty hard metric. The campaign brings tears to the eyes – but, more importantly, after six years of missed targets, teacher recruitment is now 20% ahead of target. (Great) advertising works, shock.
This is scalpel-like in its elegance and precision. It won three Grands Prix at Cannes and will be a hot contender for an effectiveness Lion this year. The most exciting campaigns are often those that find new ways to solve what seem like familiar challenges – Host/Havas’ solutionis a dazzling example of just that.
Havas New York
I love this campaign for TD Ameritrade – embedded in the digital ledger of the Bitcoin blockchain, it is the world’s first permanent piece of advertising. It drove millions of media impressions and a 26% increase in new accounts open. All for an ad cost of $23.15. That’s ROI. As a former colleague used to say: do your best work for your biggest clients.
How much are digital buyers in Western Europe’s main markets spending online?
Retail ecommerce sales in the EU-5—France, Germany, Italy, Spain and the UK—are expected to pass $325 billion this year, and surpass $400 billion in 2022.
What patterns emerged in digital sales during the 2018 holiday shopping season?
Participation in Black Friday and Cyber Monday has risen sharply in recent years, encouraged by retailers’ heavy discounting. Online traffic in France on Black Friday was 129% higher than the daily average during October 2018, and sales were up 265% on Black Friday 2017, according to Criteo. Christmas also remains central to the shopping season.
How many internet users in Western Europe shop online for groceries?
Eurostat reported that 32% of digital buyers in the UK and 23% of those in Germany bought groceries on the web in 2018. But those shares were substantially lower in France (17%), Spain (12%) and Italy (6%).
How is Amazon increasing its sales and influence in Europe’s markets, and how does that strategy differ from Alibaba’s?
Amazon is investing heavily in warehouses and other logistics capabilities to serve Western Europe. Since its 2017 purchase of Whole Foods, the company also aims to boost food sales and delivery, and is moving into financial services with Amazon Payment and Amazon Insurance (in the UK). Alibaba’s retail platform, AliExpress, is partnering with several regional store chains, including Spain’s El Corte Inglés, and promoting its own payment solution, Alipay.
In an unexpected nod to the future of fashion, LEGO Wear and Snapchat have just launched a clothing store with no clothes in it.
As London Fashion Week approaches, the brands have swapped traditional retail models for an augmented reality pop-up partnership to promote LEGO Wear’s first limited-edition clothing line for adults.
Though the pop-up is physically empty of everything but a plinth-posted Snapcode (the company’s in-app answer to QR codes), the Snap-triggered portal allows shoppers to enter a virtual shop with an interactive DJ booth, LEGO bouncer, arcade machine, and – most importantly – exclusive products for purchase.
Lea Sandell, Global Social Media Innovation Lead for LEGO, said: “As a brand we are exploring a multitude of digital platforms and technologies to connect with fans in fun and engaging ways.
“Our partner KABOOKI, who are launching this limited edition clothing line, has chosen to experiment with this specific channel and bring this experience to adult shoppers via an AR shop.
“This is an experiment exploring ways to bridge the physical and digital world and engage with fans of the LEGO brand – for us the core experience is still about using imagination to combine bricks in creative ways, and we see technology as an extension and enhancement of the physical experience. We’re constantly looking at ways of innovating the core physical LEGO play experiences in fun and engaging ways.”