Primer On Artificial Intelligence in Digital Marketing

What does Artificial Intelligence in Digital Marketing look like today

Why do Digital marketers need Artificial Intelligence?

The short answer: To make their lives easier. Marketers have depended on tools and technology to automate their work and reduce manual effort for a while. Yet, there has always been a gap in terms of effort and quantifiable results. Intuition on the right audience and time to send messages aren’t enough to answer a digital marketer’s basic questions.

Who should I reach out to? What should I send? When should I send the message? Over what channel?

The answer to these questions is the key to creating engagement and growth, fostering sales and building a brand. As these questions remain unanswered for marketers across the spectrum, there is another growing trend that can help them get these answers, and that is big data.

Data is everywhere. Every customer in the digital space brings with them an amalgamation of data and is constantly creating new data for marketers to understand, process and act on. The problem is this: big chunks of data don’t necessarily make things any easier. In fact, they can make things so complicated that the first instinct is to abandon the data and go by intuition alone – but this won’t give you the right results. This is where AI comes in.

Artificial Intelligence and machine learning can understand human behavior to the extent where not only are big data sets analyzed, segmented and filtered, but meaning is also derived from them.

-Which customers hate receiving your emails and delete them as they hit your inbox?
-How can I make sense of all this data I have on our campaigns?
-Which customer would like a particular product?
– How can I personalize the user experience and make it ‘sticky’?

Using artificial intelligence in digital marketing can not only help answer marketers answer these questions, in some cases it already is. This gives back marketers time to innovate and grow their brand, rather than worry about how to automate emails to millions of customers at a time. Here’s how AI is helping digital marketers create winning products, solutions, campaigns and brands.

What does Artificial Intelligence in Digital Marketing look like today?

AI in Digital Marketing not only exists, but it has started making the lives of users and marketers easier already. From texting to visualizing business insights, the merger of big data, machine learning and AI is creating smoother and smarter experiences everyday. Here are some of the areas that AI is integrated in to watch out for and try out to make your life easier.

Natural Language Processing (NLP)

Natural Language processing is a field that focuses on the ability of a computer to learn, and be capable of processing a human language to the level where it can infer meaning and formulate responses. Understanding language, sentiments, feelings, opinions are the biggest step towards debating, challenging and collaborating. When a machine is able to learn this process, it makes it easier for brands to understand customers on a larger, more global scale rather than just as separate, local entities. Angel.co values NLP startups at an average of $4.8 million

Ever tried the Swiftkey Keyboard on your phone? If so, you’ve already used NLP technology. The team at Swiftkey wants to create a keyboard that actually learns from your typing, and can predict responses, fix text and develop a vocabulary suited to your style of typing.

lexaImage: Lexalytics

Tools

Stanford’s Core NLP suite: Works for English, Spanish and Chinese.
Netbase: For enterprise social media analytics, real time, sentiment analysis for global products

Semantic Analysis

When it comes to humans and machines understanding each other, humans are in luck because they already know how machines talk. Machines however, have a lot of learning to do. This is where semantic analysis comes into play.

semantic analysisImage: Lexalytics

 A crucial part of natural language processing, Semantic Analysis is how machines identify the basic, logical form meanings of sentences. Although this process is incomplete without taking into account context, this is still a big step for machine learning. Think of the potential of natural language processing and semantic analysis as the potential forefathers of Douglas Adams’ Babelfish. The babelfish is able to translate conversations between people in different languages over voice in real-time. All the while, there’s AI and machine learning at the core. Semantic analysis is a part of artificial intelligence in digital marketing that is already used in spell checks, social media analysis, sentiment analysis, fact extraction, summarization and more.

Tools

Datumbox: Powerful, open source machine learning framework.

Lexalytics: Sentiment Analysis, Categorization & Named Entity Extraction

Bitext: Text analysis for marketing and CRM

Segmentation

One of the most essential ways for businesses today to understand their customers is by categorizing them as cohorts or segments. Segments may vary depending on location, interests, browser and operating system, engagement with a brand or product and more. Target audiences are no longer an age or gender group alone.

filter and segment

Target audiences can be extremely specific and combine multiple criteria to offer customization and personalization. The artificial intelligence in digital marketing trend today is all about the ‘segment of one’ and how products and services are marketed to the individual or to a smaller group with more specific interests and goals in mind.

Tools

SAP Hybris: Marketing to the ‘audience of one’

Search and Filtering

If there’s one thing you do almost every day in the digital world it is a Google search. As of 2015, RankBrain, Google’s AI engine is instrumental in processing your results. From RankBrain answering your search queries and Facebook’s Deep Text creating your newsfeed to Klevu’s smart e-commerce search, neural networks and machine learning are changing the way online search works.

semantic search and filtering
Image: Agrima Infotech

It wasn’t long ago that Google’s search algorithms worked on rule-based metrics set by humans. These were easier for engineers to tweak to boost certain signals over others. With machine learning, engineers have less control on search signals and results. It also reduces the amount of human guidance involved in steering the search algorithm, as the algorithm can almost steer itself. Artificial intelligence in search is definitely here to stay.

Tools

Klevu: Self learning search powered by NLP for ecommerce stores here.

Website Design

Self designing websites? Yes, that is actually a thing now thanks to artificial intelligence in digital marketing. Although Grid still hasn’t officially launched (as I write this post), and is possibly far from making website designers obsolete, the idea of a self designing website is pretty amazing. Here’s a link to a personal trainer’s website that was designed entirely by WIX ADI. Does this mean the website will take care of its own SEO strategy too? Unfortunately not. Or rather – not yet!

Wix ADI

Tools

Grid – The first company that promised the ‘self designing website’  Has been in private beta since 2014, and still is at the time of publishing this piece.

Wix  – Artificial Intelligence Designed websites.

 

Optimization

AI is being used to increase the effectiveness of conversion rate optimization while drastically speeding up the process. AI-based tools are superior to more traditional AB testing tools, because they allow operators to simultaneously test a variety of page elements and variations with even less traffic than is typically required for a single, statistically significant AB test.

This process is also referred to as “machine learning” and involves evolving algorithms that do a better job of finding optimum combinations and isolating the richest local maximum for a solution set.

image

Image: Conversion Sciences


Instead of testing one hypothesis at a time, AI-based tools let you throw a bunch of hypotheses into the software and the evolving algorithm is able to sort and further optimize these inputs into actionable outputs.

The ultimate destination of this technology is complete, machine-driven personalization of websites and online funnels, done in a fraction of the time it takes today’s experts to achieve similar results.

Chatbots and Messaging

Messaging platforms are all the rage right now. Whatsapp Messenger to talk to friends, Facebook Messenger to reach out to your local business, or an in-app messenger on your website to talk to customers. Conversational commerce is predicted to rule the roost in the next couple of years. This means you can look forward to doing everything from catching up with a friend to shopping online, booking a movie ticket and checking in to your flight on a messenger. But if you’re messaging away all the tasks on your to-do-list, who is going to be chatting with you on the other side? Chances are it won’t be a ‘who’ but more like a ‘what’: AI powered chatbots are being built across industries using open APIs to support specific tasks that you need to get done. This may be a new era for customer loyalty and retaining customers. Fun times ahead.

chatbot klm

Image: Social Media Today

See how the Dutch airline KLM integrated a Facebook messenger bot to make life easier for their travellers.

Tools

Boomtrain Messenger: Live, real-time AI powered in-app chat and messenger for you to recommend products and content personalized for every customer.
Drift Bot: A bot to help you direct customer queries and conversations to the right teams in your organization.

Recommendations

What are the brands you engage with the most everyday? Facebook? Netflix? Amazon? If you haven’t already figured out what makes their offerings so awesomely addictive it is this: recommendations. Machine Learning and AI powered algorithms that understand every user’s behavior, activities and make recommendations based on the understanding. On facebook, every story on your news feed is a recommendation. Amazon and Netflix are more overt, offering a ‘recommended for you’ option that you can explore. Brands can now incorporate recommendations into products and content to drive engagement in email newsletters. Artificial intelligence in digital marketing can revolutionize the content of your email inbox and make your daily emails something to look forward to rather than a task to strike off the to-do list.

boomtrain recommendation

Img: Boomtrain / Up Out

Tools

Boomtrain for Ecommerce Stores, Publishers and Brands: Recommend content, products and more to your customers at a personalized 1:1 level.

Content Generation

Natural Language Generation is the process by which, you guessed it, a machine system produces articles, summaries and other content for users. LA times has a bot called the ‘Quakebot’ that writes news about earthquakes, Forbes and Associated Press use similar natural language generation tools to create financial reports and the trend is only growing. AI bots seem ideal to handle the smaller news pieces on sports and business that involve compiling simple facts. Associated Press has reported using upto 3000 bot-generated stories in a single quarter, and that number is expected to increase.

arria content gen

Image: Arria Content Generation

Tools

Natural Language Generation Systems

Arria – Content generation specializing in simplified financial reports

Automated Insights – Wordsmith creates financial reports for the associated press.

Narrative Science – Creates Forbes’ earning reports.

Business insights

business insight dashboard tableau

Image: Datalabs.au

Any brand or business that is online needs to look at metrics to grow. The best way to do this is with a dashboard configured to understand the data and numbers working in the background across your verticals and interpret them into visual insights to help business owners make informed decisions faster. Yet, it isn’t easy to put together a dashboard that works great for your business, especially when you have a million other things going on. Artificial intelligence in digital marketing can here with automated semantics. A process by which computers, browsers can create meaning out of data that users input. It can also be used to provide business insights and dashboards. In fact, there are already companies using it. As Dan Woods mentions in his article in Forbes “Most BI technology is not really aware of what it is showing end users. Data is manipulated and graphs are presented, but the BI technology is really more of a digital blender than an intelligent prep cook who can actually anticipate what you might want.” Products offering automated semantics go beyond this digital blender method

Tools

Qlik – Flexible business dashboards for your online business. Qliksense Basic is Free for upto 5 users. Qlik Sense Cloud Plus $20/month.

Tableau – A great way to see and understand your data better. Get their free trial here.

Metric Insights – Helps you focus immediately on critical changes in your data and take action.

Sales Follow Ups and Process

sales automation

Image: Conversica

The brick-and-mortar store, the online store, the e-commerce store, the product, the SaaS – they all have one thing in common: A sales team. Innovations that help sales are innovations that help the entire organisation. Anything that makes the sales team’s process more fluid and streamlined is a boon to kickstarting the customer journey and giving customers a better bond with your brand. This is why the power of AI goes beyond digital marketing to create a difference for anyone in sales. Automated sales assistants can now help you keep track of leads that may otherwise slip through the gaps, identify leads at risk of getting cold, create dashboards to help you understand your team’s performance and a whole lot more.

Tools

Conversica: AI power for your sales process, integrates with Salesforce, Eloqua and Pardot.


Article originally appearing on Boomtrain

Image credits : Freepik

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