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Social Media Marketing: The Role of AI in 2019

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By  Laura Jensen

We live in a world where we are incentivised to share. We digitally share our photographs, thoughts and buying habits more than ever before. There is a wealth of data available on consumers and if brands want to capitalise on this through their social media marketing, they need ways to collect and understand it.

However, the need for this data is far surpassed by the fact that it is unwieldy for brands to manage – the volume and velocity of data alone can make it a monumental task to understand. That is why the industry is changing and adapting to make sure this data is much more accessible.

As we’ve seen in the digital marketing sector as a whole, the use of artificial intelligence (AI) is increasing rapidly. With applications from voice search to chatbots, there’s a wealth of information that AI is already harvesting. But, there will be so much more it can do with social media in the future.

Assisting with social media marketing analytics

Steve Wozniak, when asked what his dream product would do, said that he’d love something that would give him “more time”. When a 400-millisecond Google delay results in 8 million fewer searches, the speed to insight needs to be lightning-fast.

Companies like Brandwatch, which provide a social listening service, are looking to use AI as a way to reduce the number of hours that social analysts spend looking at brand data. Instead of an average of 3.2 hours a week looking at basic analysis, social analysts could get on with the bigger things while AI makes that data easy to understand and easy to access across an organisation.

The way Brandwatch does this is by analysis the peaks and troughs in the charts and pulling together data from a number of different sources. This is then used to work out why charts may have peaked at a particular point – maybe a social post coincided with a news event from the same industry that drove new viewers to that channel. These AI insights make reporting on social media marketing far more straightforward, since they take out the guesswork of social analytics.

Integrating customer experience with social apps

As with chatbots, AI is becoming more of a feature on social channels, integrating customer care and social analytics through customer service.

As Donika Ruseva, the Digital Owner Experience Coordinator from Jaguar Land Rover, says, “There’s no better way to show off your brand than good customer service”. Many brands use automation to implement holding messages for complaints and comments on social media, to varying degrees of success, but there’s more that can be done with social and customer experience.

Messenger apps, such as Facebook Messenger and WhatsApp, aren’t just for personal conversations anymore, but have become social media marketing platforms in themselves, providing access to both commerce and service apps. Personal banking apps, like Cleo and Plum, can help you save or manage your spending, while retailers like Made.com have created a conversational commerce experience for their customers. While these apps already exist, there’s a lot of scope in 2019 to see more businesses from different industries embracing this new use of messenger platforms.

From these AI apps, businesses can gain information on what their customers are primarily using them for, what aspects are important to them, and what trends occur on a regular basis.

AI and customer care

Supported by AI, businesses can achieve the quick, responsive and transparent response times that today’s customers expect. What’s more, AI can analyse what customers say in tweets, posts or comments.

Using AI to analyse sentiment and recognize key terms in messages to identify positive or negative feedback is already available, but there’s much more that AI can do for the customer care aspect of a business.Many AI systems have machine learning and natural language processing (NLP) capabilities, and these are key to real-time self-service on customer service platforms. AI can respond to automated queries quickly and generate responses with accuracy and speed that humans can’t match; this is especially effective, as we’ve mentioned before, when applied to chatbots on messenger services.

There are a number of other services that AI can provide in the customer service sector, such as providing an easier way to identify customer issues on social by processing and learning from gathered information, defining customer behaviour patterns, such as when or how they might complain or talk about a product, responding with suitable solutions, products or discounts after receiving complaints or messages, and much more. We’re looking forward to seeing more intuitive measures, developed over the next year and beyond, applied to social media.

By Laura Jensen

Sourced from Business 2 Community

 

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Predictive Analytics and AI Drive Up Customer Lifetime Value

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By Matthew Kelleher

We focused our efforts on seeing whether using Predictive Analytics combined with AI driven marketing automation can help improve the customer experience around the key stages of the customer lifecycle – prospect’s first purchase, second purchase, multi-purchase, VIP and churn. Our strategy was to improve marketing performance at each of these stages by using Predictive Analytics to understand where each customer is on their own journey.  When the brand understands the customer’s next likely action, they can specifically target those individuals with more effective comms, ultimately, driving up total customer lifetime value.

Results at each stage of the lifecycle have been excellent. For instance, one brand saw an increase of 83.5% in second purchase rate. This, and other case studies, can be found here. Anyone who attended my presentation at either Technology for Marketing or Festival of Marketing recently, would have seen me present the outcome of the longer analysis to see if they could improve Customer Lifetime Value. For those of you who could not attend, you will have to wait for the release of the new case studies to the website in the next couple of weeks.

The obligatory Q&A session followed my presentations at both these events. But to be honest, I always find these questions instructive and rather good fun. Too often, and I’m not alone in this, I get carried away with what I want to say, and questions illustrate key elements that I’ve missed! So, these were the six questions that were asked (although I must admit I thought there were more) with a few more thoughts than I had time to give on the day.

  1. How has GDPR affected your data gathering? How did you fight an increase (if any) in unsubscribed customers?

    Whilst it has felt like forever, the period since May 25th is still, in the grand scheme of things, relatively short! Our impression is that, in general (can you see me caveating this response very heavily!) the long-term impact on sign ups and consent is relatively little. However, for some organisations their ‘re-permissioning’ experiences have been fairly disastrous. For instance, a database of active contacts of 500,000 reduced to 6,500 (if you are in this group then you are not alone). It’s not the objective of this blog to cast aspersions on the quality of advice given to some organisations, all I can really say is that without the correct permissions, processing data for comms or even for Predictive Analytics is not possible. There are minimum amounts of data required to make Predictive Analytics work, so for many organisations with smaller databases Predictive Analytics may not work and the issues surrounding GDPR only serve to increase that group.

  2. Do you have an example of using Predictive Analytics for recruitment initiatives – getting new customers rather than increasing the value of current customers?

    RedEye has not worked with any organisations to develop models around acquisition. However, our whole strategy is built around recent prospect/customer behaviour as the key driver for predicting their next likely action. Marketers can better understand how an individual prospect or customer is behaving in relation to their brand. By tracking as many interactions, across as wide a number of channels as possible, this can then be compared with the typical behaviour of customers who have completed certain journeys. And this is applicable to many different market sectors.

  3. What were the actions that came out of the predictive model to reduce churn. How were they implemented?

    25 minutes is a very short amount of time to pack in a lot of things. One that I often leave off the list is a detailed description of the treatments employed at each of the stages. But there is a very specific reason for this… the platform RedEye has developed provides the data to the marketer, and it is up to the marketer to then leverage this information. They know their brand and customers better than anyone else. A review of the treatments used by Travis Perkins would be a completely different presentation. Every brand will develop specific treatments and the insight of what Travis Perkins did is therefore of less relevance when we’re looking at how the system was plugged together to provide the outcome. I often say ‘if you knew a specific customer was likely to never buy from you again – what would you want to say to them?’. Every marketer would have a specific answer to this, I am sure!

  4. How did you link website behaviours to an individual? Was it logged in users only?

    At FoM I briefly shot off an answer, which was that we utilise a tag management solution, which was a bit blasé. The RedEye solution has always been built around a personalisation capability centred on the value of an individual’s browsing behaviour, which is also at the core of our approach to Predictive Analytics as described above. We then link this to channel engagement information, transactional data and any other type of data a client has that has a personal identifier of any kind. It is this data that is at the core of the CDP function and therefore the bedrock of Predictive Analytics. With regards to the issue of ‘logged in’, no, the customer or prospect does not need to be logged in, they just have to have given their consent.

  5. Did any of your clients face major hurdles in pulling together all the data from siloed and legacy data pots? If so, how was this overcome?

    I would say that the vast majority of organisations that RedEye work with have internal hurdles with regards to data silos. Some clients who want to input more data find they are restricted by internal systems, and there is very little that RedEye can do to overcome these bottlenecks. But assuming that the data is available somewhere in an organisation, the CDP is there to help marketers resolve these issues. We try to make this work more effectively in two ways. Firstly, we create easier ways to format data into the system, using simple connectors to input (and export) data. And secondly, we offer support staff to help this happen for clients who are resource strapped.

  6. Which is the best CDP you would recommend for publishers?

    If I remember this question from the day it was asked by Nish! Well Nish, as an executive of RedEye I would say get in touch with us! But being a bit more professional, and having asked my colleagues on the Customer Data Platform Institute I would recommend BlueConic and Lytics who I’m informed have good experience working with publishers.

If anyone else has any other questions I would be delighted to do my best to answer them, get in contact with me here.

By Matthew Kelleher

Sourced from Digital Doughnut

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The Enormous Power of AI and Chatbots for …

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By Alice Berg

The bots are here and they here to stay. See, despite the chatbot phenomenon has gained ground only a few years ago, it has since become a full-on revolution worthy of the attention. In fact, by 2024, the bot market size is expected to exceed $1.34 billion. And as you ponder on that, it is also important to note that in 2019, at least 40% of large business ventures will implement the use of chatbots.

Let’s take a look at some AI applications in business in 2019 and beyond.

Chatbots and AI in Customer Service

Presently, bots have already delivered impressive results in customer service. Many businesses have rolled out chatbots to help them in distributing useful information and engaging the customers. For instance, Starbucks uses a system that allows customers to easily and quickly place orders using voice commands. The good chatbot will tell you the total price of your order plus when it will be ready.

Another noteworthy customer service company that uses bots is Lyft. Customers of the service can use online chat (Slack or Facebook) or AI voice chat (Amazon) to request for rides on the service. Lyft’s messenger bot offers the customer vital details. It shows the car model, a photo of the license plate, and the location of the driver.

Here are some practical ways you can use bots in your customer service business:

In the Automation of FAQs

Ask anyone if they read the FAQ section of a website, and you will probably get a hard and repetitive “no.” Rather than customers reading the questions, they would opt to email the company their queries. By leveraging chatbots and artificial intelligence, businesses can use appropriate documents to respond to any relevant questions.

As the Internal Help Desk

When an external customer service agent does not have an answer to a customer’s query, logically they would refer to the internal desk. And more often than not, this desk has to respond to the same questions over and over again. By using bots, internal customer service agents will not have to respond to common concerns.

In Offering Confident Responses

Interactive bots can ascribe a confidence score to their response. And if the score is below the threshold you had set, the bot will automatically contact a live agent and come back with a more satisfactory answer. In turn, the bot through Machine Learning can respond to similar queries in the future.

AI in Online Marketing and E-commerce

Some players in e-commerce have already started leveraging AI, and by the end of 2019, we can expect mainstream acceptance of the same. E-commerce companies such as Sephora, Asos, Sun’s Soccer, 1-800-Flowers, and Nitro Café are some of the companies that are already bringing in dollars in profit by deploying bots.

So, how can e-commerce stores and marketers use bots? For one, they can be used in customer support. Personalization is the key to every marketing strategy. And so far, bots have proven to be quite useful in providing personalized responses as compared to email or social media. People can express themselves much more freely when talking to chatbots. Therefore, to connect more with your customers, you can use a bot to interact with them and build or improve brand loyalty.

Another way e-commerce players are using artificial intelligence is in building interactive sales funnels. Marketers can use AI to group their customers and sell their products or services. A bot offers an opportunity to be dynamic and engaging. If a customer declines to try your service or product, the program can analyze the possible reasons to avoid the cases in the future.

You can also substitute emails with AI. By using a messenger chatbot, you significantly increase your click-through rates as compared to email. Most online marketers are already using chatbots to get information about visitors on their site as pop-up messages.

Some other benefits of using artificial intelligence in e-commerce include recouping abandoned carts, upselling after purchases, generating leads, providing useful AI algorithms for product recommendations, and boosting customer retention.

“83% of people who shop online need support, 56% prefer to get a text message, and 38% of people consider chatbots are even more useful. It is, therefore, good business to invest in a bot as an online entrepreneur,” – noted Andrew Ortiz, marketing specialist at Skillroads.

AI Online Chat in Tourism and Hospitality

Chatbots are already among the top technology trends in tourism and hospitality businesses. And in 2019, there are expected to be adopted on a wider scale. Bots are helping companies in this sector to reduce costs while also providing an excellent user experience. So far, bots have helped tourism and hospitality companies increase customer satisfaction. Some of the firms that have already witnessed the good results of using AI applications include Marriot, Snap Travel, KLM, Waylo, and Wynn.

You can use a bot in your business for different reasons. For instance, you can use it to engage customers before, throughout, and after the trip. Bots can send prospective and existing customers links to personalized content on hotels, destination sites, top restaurants, and so forth. Once a customer has booked a room, for example, a bot can come in to help them check in, request service, suggest activities, order meals from the restaurant, and more. Upon checking out, a bot can assist in collecting feedback and comments from customers.

Bots can also help in personalizing the customer experience. By doing this, they eliminate competition based on pricing. Customers often consider factors such as location and brand along with the price when choosing hotels. A bot can thus assist you to send out personalized packages to your customers and appeal to them. They help you put together all activities that interest the target audience and market the package to them specifically.

Chatbots and artificial intelligence can also be used in anticipating customers. By using predictive analysis, a hotel owner can identify future patterns and send out targeted campaigns to customers. For example, in 2014, Roof Inn used flight and weather data to predict the customers that were likely to face cancellations of their flights. In turn, they were able to send out campaigns on mobile devices to customers in locations that were likely to experience harsh weather. So what can we take from this? Bots can help in anticipating problems and addressing them way before they happen.

Artificial Intelligence in Financial Services and Banking

Financial tech companies such as Fintech are already causing waves in the industry by introducing bots. By 2020, it is expected that 85% of customers will use Fintech Chatbots to manage their bank transactions. Currently, some big banks are already using bots. These include Visa, MasterCard, Chase, American Express, Capital One, PayPal, Barclays, Ally Bank, and Bank of America.

So, how are financial companies using bots? First, Chatbots and AI are helping in smart messaging whereby they warn customers about dangers or other issues affecting their accounts. Second, they can also give you personalized tips on things you can do with your finances. Moreover, they can help you know how you are using your funds, how you are repaying your loans, and how you can save more money. And not to forget, bots are offering customers around-the-clock support and useful insight that improves customer experience.

It is important to note that, bots are expected to save financial institutions over $8 billion per year by 2022.

AI in Human Resource Management and Hiring

One of the big beneficiaries of AI has to be HR and recruiting. Bots have become integral in virtually all aspects of the employee lifecycle from sourcing, to screening, to interviewing, and finally to hire.

Employers are also using bots to boost customer engagement. These systems act as a bridge that connects employees to the existing job systems thus giving them better experience at the workplace. Maya is one of the companies that is automating all the stages of recruitment. SAP, Wade & Wendy, Loka, and SGT STAR are some other firms that are also using bots.

AI in Voice and IOT

Voice-powered assistants are increasingly becoming popular. Alexa, by Amazon, is one of the pioneer voice assistants and accounts for up to 70 percent of the market share. Come 2020; it is projected at least 128 million smart speakers will have been sold.

Final Thoughts on AI for Business

As an entrepreneur, AI is a tech trend to watch out for if you are keen on staying relevant, growing your business, and making a profit. Chatbots are cost-effective, time-saving, and most importantly give your customers a personal touch.

By Alice Berg

Alice Berg is a career advisor, who helps people to find their own way in life, gives career advice and guidance, helps young people to prepare for their careers. You can find Alice on Twitter and Medium.

Sourced from RUHANIRABIN

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The AI Breakthrough in Service Industries

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Among the service industries to benefit the most from the AI breakthrough are the Banking, Insurance, Telecom, and Utility Industries.

It is now no secret that Artificial Intelligence is the next big thing. It is set to transform our entire way of life, from how we live to how we work and how we interact with one another.

In fact, we are already seeing some of the effects of Artificial Intelligence in most industries today.

Artificial Intelligence is currently being utilized in a wide variety of businesses and is widely used in many award-winning apps and software in the market, particularly in service industries, the AI role will only continue to rise.

The service industry landscape has shifted to acknowledge the importance of Artificial Intelligence.

Among the service industries to benefit the most from the AI breakthrough are the Banking, Insurance, Telecom, and Utility Industries.

AI in the Banking Industry

3D illustration of a robot hand holding for a generic credit card with NFC technology. Credit card is fictitious. PixOne / Shutterstock.com

3D illustration of a robot hand holding for a generic credit card with NFC technology. Credit card is fictitious. PixOne / Shutterstock.com

The banking industry has benefited massively from the introduction of AI systems, and will only continue to do so.

Some of the areas that have been impacted include:

–         Customer Experience

AI chatbots are all over the place in the banking industry. Almost every major bank has one. These bots have streamlined customer interactions and improved customer experience and satisfaction. App development companies have made it possible for clients to be able to ask for banking assistance and receive it without having to visit a bank at a physical location. This adds a level of convenience that customers appreciate. This is only achievable with AI.

–         Management of Customer Data

The breakthroughs of AI in the management of customer data is outstanding. For example, when JPMorgan Chase’s Contract Intelligence AI was given the task to review their 12000 commercial credit agreements, it managed the task in a few seconds. This compared to the estimated 360,000 hours manual evaluation normally took. The AI has now officially replaced humans in performing this task, freeing up more human resources for other sectors. Today, similar AI can be used to manage emails, articles, phone calls and other legal documents.

–         Banking Security

AI is changing the way banks secure themselves. Cases of money laundering have previously plagued the industry, but this will all soon change. Banks have started seeking tailored AI solutions to help them combat the vice.

AI in Insurance Industry

AI, artificial intelligence, in modern medical technology. IOT and automation. Wright Studio / Shutterstock.com

AI, artificial intelligence, in modern medical technology. IOT and automation. Wright Studio / Shutterstock.com

AI is literally shaking up the insurance industry. Today, traditional insurance and underwriting are being updated to become more efficient and more consumer-friendly through the utilization of AI technologies. Some of the changes we are bound to see more of include:

–         Micro changes

AI is slowly making it possible for insurance companies to access user data and tweak their offers to suit user behaviour. This is only going to be more prevalent in the future. For example, your car sensor may show that you have a history of reckless driving, and consequently, your car insurance rate may increase by 1%. If you are a very good driver, your car insurance rate may drop by 1%. This tweaking not only rewards good drivers but also results in more revenue for insurance companies.

–         Customer interactions

The insurance industry stands to benefit greatly from the advances being made in AI for customer interactions. Soon, we may see app development companies develop insurance apps with assistants that warn you if you engage in activities that could lower your insurance rate, or alert you when you are doing something that could boost your rates.

–         AI May Make Some Insurance Sectors Obsolete

By 2020, driverless cars will be common on our roads. This shift will bring with it many changes to the insurance industry. The much safer cars will lead to a much lower accident rate for example.

Auto insurance may stop being as lucrative, and insurance companies may have to adapt and switch to ensuring car manufacturers as opposed to individual drivers who will see no need for auto insurance.

AI in the Telecom Industry

Chat bot and future marketing concept . Customer hand holding tablet look for ticket and popup out smart phone screen with automatic chatbot message screen , airport background

Chat bot and future marketing concept . Customer hand holding tablet look for ticket and popup out smart phone screen with automatic chatbot message screen , airport background (Photo Credit: www.shutterstock.com)

The Telecom Industry benefits from the advantages of using AI on three fronts:

–         Customer Service and Retention

AI has enhanced customer service in the Telecom industry. The rise in customer service solutions such as chatbots has eased communication between customers and their Telecom companies. This leads to better user experience and satisfaction. AI can also be used as customer service agents, where they interact directly with clients, making the customer service process more cost-efficient.

–         Sales and Personalized User Experience

AI has also helped companies in the Telecom Industry to improve customer retention and boost the amount of revenue earned per user. The immense power of AI can be harnessed to offer personalized product recommendations to clients, assessing the type of call or data packages that suite a potential client pre-sale to increase sale success rates, and analyzing social media, brand image, and customer feedback and offering recommendations to help make the company better.

–         Network Analysis

AI plays a huge role in the network maintenance of Telecom companies. Optimized networks are a necessity today, especially due to increased data consumption. Telecom companies need to adapt and cater to their users’ needs. In the Telecom Industry, AI is being used as a network maintenance solution with a focus on the creation of self-healing, self-learning, and self-optimizing networks. This approach has proven to be future proof and sustainable.

AI in the Utility Industry

Unrecognizable corporate water utility executive managing meter data via advanced metering infrastructure solution. Industry concept for AMI, SaaS, managed services, MDM, IoT, network as a service. LeoWolfert / Shutterstock.com

Unrecognizable corporate water utility executive managing meter data via advanced metering infrastructure solution. Industry concept for AMI, SaaS, managed services, MDM, IoT, network as a service. LeoWolfert / Shutterstock.com

 The Utility Industry is already gaining a lot from the application of AI technologies. For example, AI is being used in:

–         Yield Optimization

In the utility industry, total yield equals total revenue. An increase in total yield usually means an increase in revenue. The application of AI technologies has led to optimized yields. For example, in the power production sector, power generation efficiency can be optimized by using real-time adjustments across their assets to maximize output while minimizing resource use.

–          Predictive Maintenance

Maintenance is a huge deal when it comes to the utility space. With the help of AI, drones equipped with deep learning algorithms can be deployed to help automatically identify defects and potential failure points, predicting when maintenance will be needed. This does away with costly and inaccurate manual inspections.

–         Customer Insights

AI can be used to help utilities maximize margins and minimize consumption. They can also help craft individual customer offers or deals on their services that will allow utility companies to gain new customers, create a larger user base and boost customer loyalty.

By 

  • Rilind Elezaj is an experienced Digital Marketing Specialist with a demonstrated history of working in the marketing and advertising industry. Rilind possesses a strong entrepreneurial mindset and has devoted his career to enhancing the sphere of digital marketing. In his methodological approach, Rilind integrates web development and other digital marketing solutions to create hybrid strategies that bring the best results.

Sourced from TALK IoT

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Does Your AI Need a Personality?

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By Mike Moran 

If you are Amazon with Alexa, clearly your AI needs a personality–Alexa wants to be your helpful friend. You talk to her. She talks back. No problem. But does your business AI need a personality? Everywhere you look, someone thinks it does. IBM wants you to love Watson. SAP has Leonardo. Salesforce has Einstein. For you big companies left: Fermi, Curie, and Plato are up for grabs, I think.

Do we need to anthropomorphize AI to make it marketable? Palatable? Acceptable? Approachable? Is this an important part of AI adoption, or a silly phase we will look back on with disdain? I personally think it’s overkill and might actually backfire as we all become better sophisticated, learning that AI isn’t anywhere near as smart as Albert Einstein, Leonardo da Vinci, or even IBM founder Tom Watson.

Maybe we should be looking for real genius, like the guy who invented soft-serve ice cream, Tom Carvel. I can hear him now, “Look at this AI. It’s beautiful AI. It’s the best AI money can buy.” So, maybe we should name our AI “Tom.” Yeah, not sexy, I know, but that’s the point.

AI is becoming embedded in every kind of software you can imagine, and, at it’s best, it isn’t noticeable at all. It just does the job better.

I think Google has the right approach. Yes, you say “Hey, Google,” when you want to talk to your Google Assistant, but there are countless AI component inside dozens of Google products, starting with Google Search, that don’t need a name. They just work better.

To me, that’s what we really needed. AI that works better, rather than has a cute name.

Full disclosure: I am the Senior Strategist at Converseon and SoloSegment, both of which have AI that works, without any cute names.

By Mike Moran 

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Sourced from B2C Business 2 Community

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How AI Helps Marketers Build Customer Profiles and Drive Revenue

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By  Derek Andersen 

Forbes recently stated that 80% of enterprise companies are investing in artificial intelligence (AI) solutions today. AI is a machine’s ability to imitate intelligent human behavior by perceiving a set of inputs and processing that information in order to reach a desired outcome.

In the martech space, companies are utilizing AI to build customer profiles, resulting in more precise ad targeting as well as unprecedented customization. Below are three recent examples of how companies are using AI to build customer profiles and drive revenue.

1. Teleflora Uses AI to Deliver Personalized Product Recommendations

A recent article in Direct Marketing News details how Teleflora, a leading floral arrangements vendor with more than 15,000 member florists in the US and Canada, uses AI to build customer profiles and provide a personalized touch.

Source: Teleflora.com

When Tommy Lamb, Teleflora’s new director of CRM and loyalty, joined the company, he immediately realized their marketing strategy was underdeveloped. Since customers typically only used Teleflora at spread-out points in the year, the company needed strong remarketing and customer service to build brand loyalty. But rather than providing personalized offers, they only utilized a few generic holiday email campaigns.

A retail marketing platform called Bluecore gave Lamb and Teleflora the AI capabilities they needed in order to execute a three-pronged personalization plan:

  1. Teleflora first created more comprehensive customer profiles by combining their product data with their individual customer data.
  2. Next, Teleflora paired Bluecore’s machine learning capabilities with these comprehensive profiles to anticipate the future purchases of various audience segments.
  3. Finally, Teleflora integrated advanced analytics, allowing them to identify best-selling items and other purchasing trends.

This AI strategy allows Teleflora to accurately anticipate customer needs. They can target customers who are ready to buy and make personalized recommendations, driving customer loyalty and ROI. Then, their analytics solution allows them to view the results and promote high- or low-performing products accordingly.

2. BMW Leverages AI to Personalize Ad Spend and Lower its Cost-Per-Acquisition

In order to execute a recent campaign, BMW Mini worked to connect and organize its data into an actionable format. Its goal: to target adults searching for a premium vehicle who had shown interest in the BMW brand.

Source: BMWBy partnering with ad agency Universal McCann, BMW was able to leverage its first-party data—which included people who had visited the BMW website or were already in their CRM system. BMW used this data to enhance its existing search strategy, ensuring its ads delivered relevant messaging to interested car shoppers.

BMW then utilized an AI solution to optimize the efficiency of its targeted ads. Over time, this solution optimized BMW’s ad targeting so the messaging would reach the right person, based on factors like time of day, previous searches, and BMW website visits. As a result of this strategy, BMW Mini’s conversions tripled and their cost per acquisition declined by 75%.

3. Comfort Keepers Utilizes AI to Target Caller-Ready Audiences

Comfort Keepers, one of the nation’s leading providers of in-home care for seniors, uses AI-powered conversation analytics to understand what happens on calls to each of their 450+ franchisee locations. Since phone calls make up 70% of their marketing conversions, they analyze the calls to determine who each caller is, if they are a quality sales lead (vs. a non-sales call), and if they converted to an appointment or customer.

By using this conversation analytics data, Comfort Keepers is able to fully gauge the success of their marketing efforts and prove it to each of their franchisees. Not only are they able to identify the quantity of the calls their campaigns drove, but they can also understand the quality. For example, rather than simply saying “we drove 2,000 calls this week,” they’re able to identify how many of those calls are potential new customers versus current customers. This gives them a full picture of the ROI from each of their campaigns to each location.

As a next step, once Comfort Keepers understands who converted on their calls and who did not, they can use that same conversation analytics data from AI to retarget their prospects with search, social, and display ads and use good callers in their lookalike campaigns.
Read more at https://www.business2community.com/marketing/how-ai-helps-marketers-build-customer-profiles-and-drive-revenue-02091198

By  Derek Andersen 

Sourced from Business 2 Community

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How Can Your E-Commerce Business Leverage The AI Trend?

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By Stankevicius MGM

AI-powered email marketing tools are revolutionizing the way email is built.

Business owners would agree: email still holds the crown as one of the most valuable ways to connect to customers. And rightfully so, as, according to the Direct Marketing Association UK, for every $1 spent, email marketing generates $30 in revenue. However, approaches to email campaigns remain largely outdated. The result: the more emails users receive, the more they are ignored, which has led to a decline in email use, at least among millenials.

Thus, AI has emerged as an increasingly important part of email marketing for businesses across the globe. And thanks to AI, email marketing is getting a revamp which solves many challenges that e-commerce business owners have been facing.

In today’s era of micro-personalization and increasing data protection demands, e-commerce business owners find it difficult to adapt to the ever-changing rules of email marketing. Too often, in order to maintain the competitive edge, entrepreneurs face the need to hire additional help such as marketing assistants or agencies. Now, with a new generation of smart and simple AI tools that support most e-commerce platforms, an e-commerce business owner can supercharge their email marketing campaign single-handedly. Instead of learning new rules or bringing on board new hires, AI does the work for the e-commerce business owner.

Here’s how AI raises the bar for e-commerce email marketing.

Predictive Personalization

Personalization means to email marketers what the Holy Grail would be to Indiana Jones — rare, elusive, seemingly unattainable. Not anymore, thanks to AI.

AI helps the business owner to identify the behaviors and events that should trigger email-based marketing communications, determining which offers will produce the desired results.

This level of personalization would be all but impossible to achieve without AI.  “Machine learning helps AI-based email tools to understand what is most meaningful for a specific audience,” says Igor Solovyov, founder and CEO of Triggmine, an intelligent AI-powered email marketing platform.

Powerful Ambition

Triggmine’s goal, among others, is for the platform to segment and target audiences using “natural language technology to select the words for subject lines, body copy and calls-to-action. This way, the message not only sounds like it has been written by a human, but is also consistent with the language generally used by the e-commerce business”. While that ambition is certainly powerful, it is not unwarranted. When tech research firm Gartner gave its predictions for tech in 2018, its first was that machines would play a role in writing copy because of the unique insights big data can provide. Intelligent AI-powered email marketing platforms like Triggmine’s are paving the way for a revolution in the way E-Commerce is practiced.

Seeing the potential of AI for the E-Commerce business owners that they work with daily, Triggmine made the decision to switch to AI due to the speed, precision and specificity that an AI platform can provide its customers. For small and medium business owners who don’t have time to handle their marketing activities, this allows business owners to focus on running their business whilst optimizing their marketing campaigns, for minimal effort.

AI tailors messages for various segments of an email list and delivers suggestions precisely for a particular niche or person. AI-powered email applications use big data to suggest the type of content that complements each stage of the buyer’s journey. By analyzing behavior and clickstream, AI essentially replaces the function of not just the copywriter, but the marketer too.

Time It Right

For years, marketers have recognized that when they send emails has meaningful impact on open rates and click-through rates.

For example, an email recipient in Paris might be less likely to open an email that is delivered in the dead of night because the send time was optimized for subscribers in the U.S. Central Standard Time zone. For this reason, some email marketers segment their subscribers in an effort to ensure that their emails are delivered to each segment at a good time.

Besides, the attention span of customers is so short that if the message arrives in customer’s inbox at the wrong time, it gets buried or even deleted straight away. AI combats this peculiarity in a certain way. By determining when a particular customer is most active online, AI can judge when there is a higher chance of the customer reading and acting on the message. The AI-powered marketing tool then acts even more intelligently: instead of emailing large segments of email list, it optimizes send time on a per-subscriber basis. Doing this manually would be nearly impossible, but it’s easy work for AI.

Historically, email marketing has been mostly manual, strongly oriented towards campaigns. With the arrival of AI, email is laser-focused and single user-oriented. This of course begs the question, what‘s the next frontier for e-commerce email marketing? The answer is clear: optimizing the mobile experience. According to recent studies, by 2020 there will be 6.1 billion smartphone users worldwide. That’s nearly as much as the current population of the earth!

For this transformation, marketers need a helping hand and what will be better than a smart robot? Artificial Intelligence tools such as Triggmine are fundamentally reshaping different marketing channels such as email marketing — and there’s more to come.

Feature Image Credit: Courtesy of Stankevicius MGM 

By Stankevicius MGM

Sourced from Entrepreneur

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How AI Is Changing the World of Advertising Forever

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By George Beall.

For how much Hollywood loves remakes, I’m curious to see what a futuristic Mad Men is going to look like. Don’t get me wrong; I’m not expecting to see robotic Don Draper, who writes poignant lines of copy aggregated from data points all over the world (that’d be cheesy and boring). Rather, I’d be more excited to see how technology is going to change the world of advertising for good.

A lot of people might think that under the reigns of Artificial Intelligence every job will suddenly be replaced by a robot. However, the core component of advertising is storytelling, which is something that requires a human touch. Even more, AI isn’t going to replace storytellers, but rather empower them. Yes, the world of artificial intelligence is about to make advertising more human. Here’s why:

From Madison Avenue to Silicon Valley

It’s no secret that the advertising world goes giddy over any innovation in the tech realm. After all, a big portion of how firms gain an edge in their industry is by being up on the latest and greatest, as well as demonstrating a capacity to look at how new practices can be applied to client campaigns. And when it comes to AI, a lot of major agencies have already situated themselves ahead of the curve.

The interesting thing to note here isn’t necessarily that these agencies are using AI in general, but rather, how they’re using it. For example, the link above notes how a few firms have teamed up with AI firms to work on targeting and audience discovery. While these practices have been implemented long before, Artificial Intelligence has been accelerating the process. However, even with major players teaming up with the likes of IBM Watson, smaller agencies and startups have been on this trend as well.

An excellent example of this is the company Frank, an AI based advertising firm for startups. Frank’s goal is to use AI in the same manner of targeting mentioned above, only offering it to those businesses that could really use the savings. The platform allows you to set the goals of your campaign, as well as hones in on targeting and bidding efficiently. This saves time and money often devoted to outsourcing digital advertising efforts, as well as gives an accurate depiction of how ads are performing in real time. Expect players like Frank to make a significant change in how small businesses and startups approach how to use AI in their marketing.

Big Dollars For Small Budgets

One of the biggest news stories to hit about AI and advertising was Goldman Sach’s $30 million investment into Persado. If you haven’t heard about it yet, Persado essentially aggregates and compiles ‘cognitive content,’ which is copy backed by data. It breaks down everything, from sentence structure, word choice, emotion, time of day, and even can bring in a more accurate call-to-action. And for those that hire digital marketers and advertisers, this sounds like a dream come true in saving time and money. However, when it comes to writing, AI can only go so far.

While some content creators and digital copywriters might be a little nervous that AI will eventually take their jobs, that’s simply not the case. Writing involves a certain sense of emotional intelligence and response that no computer can feel. Moreover, the type of content that AI can create is limited to short-term messages. I’m not sure about you, but I’ll safely bet that no major marketing director is willing to put their Super Bowl ad in the hands of a computer. Overall, while Wall Street recognizes Artificial Intelligence’s potential impact in the creative world, it’s safe to say when it comes to telling a story, that human touch will never go away.

The Unexpected Players

Perhaps one of the most underrated things about AI is its potential to eliminate practices altogether. While we mentioned above that, yes, certain jobs in the creative field will never go away, there’s a possibility that certain processes in the marketing channel might change drastically.

For example, companies like Leadcrunch are using AI to build up B2B sales leads. While before B2B sales could rely on either targeted ads or sales teams to bring clients in, software like Leadcrunch’s is eliminating those processes altogether. Granted, this isn’t exactly a bad thing as a lot of B2B communications relies heavily on educating consumers, something a banner ad can’t do as accurately as a person. Overall, companies like this are going to drastically change how our pipelines work, potentially changing how the relationship between advertising and AI work hand-in-hand for a long time.

By George Beall

George Beall is a student at the Wharton School of the University of Pennsylvania. He has a deep admiration for true innovation and has been involved in multiple in technology startups. He is currently an active angel investor. In his spare time he enjoys horseback riding, discovering upcoming music, and binge watching Netflix.

Sourced from TNW

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