Artificial intelligence (or AI) is already changing the way we think about marketing. AI technology can optimize and accelerate many marketing tasks, improving customer experience and driving conversions.
If you are involved in enterprise marketing There’s a good possibility that you already use an AI-powered solution in your Martech stack. Many marketers are still unaware of the advantages of AI and machine learning over traditional marketing software.
You may not be fully on board yet You’re not alone if you are thinking of dipping your toes into the water. Investing in technology is a major commitment. It can also be daunting when it’s backed by complicated concepts such as machine learning algorithms.
1. Improved Personalization and Recommendations
Marketing messages are changing in how consumers interact with them. Traditional marketing methods such as direct mail and media advertising are no longer as effective.
This is because today’s consumers expect marketers to tailor messages to them based on their location, demographics, or interests. Non-personalized marketing may be ignored or not received by many.
Accenture reported that more than 40% of consumers changed brands because of a lack of trust and poor personalization. Companies that provide personalized customer service are 43% more likely to purchase from them.
Personalized marketing messages are more popular with consumers. Experian data shows that personalized subject lines make emails 26% more likely to be opened. Marketo also found that 79% of respondents to a global survey said that brand promotions are more likely to be opened if the subject lines are specific to their past interactions.
AI allows marketers to personalize communications at an individual level, rather than targeting a generic group of people as they did in the past.
The technology predicts customer behavior using intelligence gleaned from past interactions. This allows marketers to send marketing communications and content that convert leads into sales at the most effective times.
Also read: How Artificial Intelligence Helps Business Grow
The personalized recommendations offered by sites like Amazon and Netflix will be familiar to most people.
These recommendation engines have evolved over time and can be astonishingly accurate for users who have been using the service for a long time. Amazon, for example, has a record:
- Every purchase you have ever made
- History of product browsing
- These are the addresses where you have lived and worked.
- You’ve always wanted items
- You’ve seen TV and heard the music.
- Apps that you have downloaded
- You’ve left reviews and product ratings
- You’ve used devices to download ebooks or watch movies on.
- All the questions Alexa has asked if you have an Echo
This information can be used to make product recommendations based on your interests. Past purchases and other people who bought the same products as you.
If you have previously purchased a printer, Amazon will recommend that you purchase cartridges and paper. You might find baby clothes and toys in your recommendations if you have ordered prenatal vitamins and stretch mark cream.
This is all powered by DSSTNE, an AI framework that has been made open-source software to enhance its deep learning capabilities.
Gartner predicts, however, that although 90% of brands will employ some form of marketing personalization before 2020, many will not be able to create optimally personalized content.
AI is the answer to improving personalization as well as producing better content. Machine-learning algorithms allow marketers to create hyper-personalized customer experiences by analyzing customer data.
2. Dynamic Pricing
Discounts are a surefire way of increasing sales. However, some customers will purchase with a smaller discount or no discount.
Artificial intelligence can be used to dynamically set prices for products based on demand, availability, customer profiles, and other factors. This allows you to maximize sales and profit.
The website camelcamelcamel.com allows you to see dynamic pricing in action. It tracks the Amazon product prices over time. A graph shows how the price fluctuates based on popularity and season.
Have you ever tried to find a flight only to return home and buy another one? It was only a few days later that it was discovered that it had gone up by a few hundred dollars. This is another example of dynamic pricing at its best.
3. Chatbots for Customer Service
Facebook Messenger, WhatsApp, and other messaging apps are becoming a popular way for customers to reach companies. However, it can be costly to ensure that the accounts remain staffed with customer service representatives.
Chatbots are being used by some companies to answer customer questions and give instant responses at all times of the day and night. Chatbots can be programmed with pre-recorded answers to common questions, and the ability to redirect the conversation to a human agent for more complex questions. This reduces customer service time and makes it easier for agents to handle more personal conversations.
Chatbots such as Siri, Google Assistant, and Cortana are becoming more familiar and even preferred to real people. AI language processing algorithms have advanced significantly in recent years. This makes it possible for machines in customer service and sales roles to replace human agents.
Chatbots can be more cost-effective than having more people handle inquiries. They also have the ability to do so in a more efficient, sometimes even more human way. Chatbots are always polite, friendly, and engaging, unlike humans.
Also read: How to Use AI Technology for Your SEO Strategy
4. Search Engine Optimization
Search algorithms are constantly improving, from simple database product searches on eCommerce sites to more sophisticated search engines like Google that are used daily by millions.
Searches can be integrated with AI to detect misspellings and suggest alternatives (“did you mean …?”) This may be affected by your browsing history or shopping habits.
Google is getting more sophisticated in determining searcher intent. For example, if someone searches “Apple”, are they searching for information about apple, the technology company, or the record label.
Search engines can tell if someone is searching for “coffee shops” on their phone. They know that they are looking for coffee shops within a few miles of the user’s location, not general search results.
As the number of AI-powered devices increases, special results like shopping and Google My Business results are providing better user experiences for searchers. Voice search is also becoming more common as voice search becomes more common.
Furthermore, voice searching is growing rapidly with smart home speakers and mobile internet usage. It is expected that this trend will continue.
AI is required to understand complex speech patterns and recognize meaning in spoken search queries. These are quite different from traditional typed searches.
Marketers can also make use of AI to optimize content for voice searches, which will help to increase SEO and site traffic in this voice-operated digital age.
5. PPC Ad Optimization
A/B testing is a traditional method of optimizing marketing messages and display ads. However, it can be tedious with an inordinate number of variables to test, which means that it takes up much time and resources. AI algorithms can automatically optimize your ads based on conversions and interactions.
However, they are more resistant to advertisements. Publishers and advertisers have found it more difficult to deal with Ghostery and other apps that can detect and block tracking technology. The impact on publishing is shocking: Revenue losses of $35 billion will be realized by the end of the year, assuming that adoption rates continue to rise.
Unilever and Havas, agencies such as Havas, have previously decided to stop YouTube and Google spending due to ad placements that were not in line with “undesirable and unsafe content”. Aside from the questionable reporting of viewability and rising instances of ad fraud, this is making brands and agencies more cautious about how much they spend.
The customer journey starts at the point of interest. The holy grail is how we interact with customers to provide the most relevant information to them at the right time to maximize their response rate. This digital landscape testing and implementation field have seen practitioners succeed in applying techniques that maximize performance over the past decade.
Google realized that it is impossible to know what ads work by simply measuring the performance of all campaigns. Google has moved to conversion metrics (CV) because Click-through rates (CTR) are a misleading term. It is no longer a measure of true intent. The intent is not a collection of behaviors in an ad format. It’s not by analyzing the events of the buying funnel that are responsible for the buying behavior. Here’s a brief introduction to Artificial Intelligence, and why it is the next step in the CMO’s journey.
AI advertising optimization is also used on social networks like Instagram. Algorithms will analyze which accounts a user follows and show them the most relevant ads. This results in a better user experience and an increase in the ROI of the advertiser. Fewer ads are shown to people that aren’t interested.
6. Content creation and curation at scale
Content marketing offers a high return on investment. It can also be expensive. It can be costly. Gartner predicts most brands will have trouble not only gathering enough data but also creating enough content to provide a personalized experience for every user.
While machine-generated content is not new but the first attempts to create it were very difficult. Search engines may have been fooled temporarily, but humans are still able to read the original attempts.
Artificial intelligence for content creation is now so sophisticated that Stylist magazine published three articles generated automatically by it. ”
AI can help speed up content marketing and optimize it in many different ways. AI can help speed up content marketing and optimize it in many different ways.
Although you may not trust machines to create your content, they are still helpful for small tasks such as generating social media posts. The Washington Post uses Heliograf in-house reporting technology to create basic social media posts as well as news stories.
Computers can also come up with formulaic headlines that are easy to understand, especially if they’re classified as clickbait.
Although you may not be considering replacing your copywriter with AI software, we might be closer than you realize. Many global brands, including Forbes, now publish content that is at least partially generated by AI.
The use of AI speeds up content production and allows marketers to scale their content marketing. 47% say that scaling up content marketing is their greatest challenge.
Also read: 14 Creative Marketing Ideas for Improve Your Business
7. Digital Promotion: Optimizing the “When”, and “Where”
Digital marketing offers many new possibilities, but it can be overwhelming to manage the multitude of options. Content marketers have many options, but not all channels are equally effective for every lead.
It is possible to find the best channels through extensive experimentation but this takes time and can require a lot of resources. AI eliminates the need for you to manually choose the channels that are best suited to your campaign to reach specific leads. AI-powered software can quickly identify the most profitable channels based upon interactions with the brand.
Timing is crucial when you want to make the most of your marketing campaigns. AI eliminates the need to guesswork, experiment, or rely on industry averages like “the best day to post on LinkedIn” on Wednesday between 10 am – 2 pm. AI scheduling software automatically determines when the best time is to promote a customer’s product on each marketing channel.
8. Automated Marketing Processes
Marketing automation is a well-established technology. Email marketing software is able to automatically convert thousands of emails into one copy.
AI-powered email and automation software allow you to take things up a level and reduce the burden of decision-making. Machines can perform repetitive tasks more efficiently than AI, which means that they can do most of the work for human marketers. This allows for more time and resources to be used on tasks that involve the “human element”, such as follow-ups and communication with customers.
AI-powered marketing automation can be used to personalize customer experiences, respond to customer interactions and contact leads at the most optimal times through the channels that have the greatest chance of success.
AI can be used to assist you in deciding what content to create and when, how, and where to distribute it. Automate the entire process with one click.
You can reduce repetitive tasks by outsourcing them to marketing software. This will allow you to increase productivity and concentrate your efforts on strategic marketing planning and talking to customers face-to-face.
9. Processing Big Data
While humans are more skilled than machines in many tasks, they can also make mistakes. This is especially true when it comes down to data usage, particularly large amounts of data. AI can reduce errors caused by duplicated or out-of-date data. The software can combine intelligence from multiple sources into one database.
Many enterprise organizations already collect a lot of valuable information about customers and their industry. However, most fail to use the data that they collect.
An international survey of business leaders in North America and Europe found that only 4 percent of companies make the most of their data.
This could be due to a lack of skills or technology, as well as the fact that not enough data analysts are available. Businesses are often overwhelmed by the volume of data they have. AI is a great tool for understanding and processing data.
Artificial intelligence excels in processing large amounts of data and spotting patterns and trends. Artificial intelligence can be used to extract valuable insights from data, and to present this information in an easy-to-understand format that employees at all levels of the marketing or management team can use.
Also read: Tips for Optimizing Your Customer Service Approach in 2022
10. Predicting and understanding customer behavior
Did you know AI can accurately predict your personality traits more than your spouse, partner, friend, or even your family members? This was one of the key insights that I gained at Pegaworld in Las Vegas, NV, a few years back.
Over 4,000 IT and business leaders gathered to discuss the role of technology in the future of marketing, sales, and customer service. Although this event featured some smart people, it was a little more technical than I see at Marketing conferences.
An audience that is still trying to solve the exact same problems as me:
- Marketers are trying to understand what it takes to reach customers effectively when ad blocking, changing media consumption habits and ad performance is a problem.
- Customer service personnel are looking to improve customer satisfaction and net promoter scores while lowering costs.
- Sales are trying to sell more in an environment that is increasingly avoiding promotional messages and business development strategies of the past.
AI can be a powerful tool for courageous leaders in customer-centric organizations to achieve their goals of personalization, better customer decision-making, and improved predictive modeling. For professionals who aren’t as busy, more sales, lower prices, and happier employees.
AI is able to personalize customer interactions and use predictive modeling to improve outcomes. The following AI capabilities are also available:
A Customer Decision Hub that automates recommendations in real-time to improve customer experience using AI
Natural Language Processing is used to analyze customer voice and email messages for mood and intentions
Self-Service Advisor that can scan the browsing history of your customer to show you different options.
Artificial intelligence-driven apps that alert retail store representatives on how to best help customers in-store. This can be done in real-time via their smartphones or tablets. Unsatisfied customers will not abandon a brand. Loyalty is not determined by the price.
This may be because customers are more sensitive to the benefits of points than they are to the cost of purchasing an airline ticket. The marketer will be able to see the potential for customer churn if all of these events are taken together.
AI allows you to draw patterns from the complexity of human intent to determine multiple drivers that can (to different degrees) influence their decisions across millions. It can vary for different products and services, at different times of the year, in different geographic areas, or with different demographics.
Machines are also able to spot patterns in data and predict what customers will do, often before they have even made a decision. AI software makes predictions based on past behavior. This is done with astonishing accuracy.
You can predict the buying habits and actions of customers to send targeted marketing messages. Then you can nurture them with a customized buying funnel designed to maximize sales.
Although this sounds complex, artificial intelligence takes care of all the work. Intelligent software can help you gain valuable insights into your customers and automatically send marketing messages at the right time to maximize sales opportunities.
AI helps you identify the most valuable leads so that your sales team can focus on them and not waste time on leads that aren’t ready to buy.
This helps you streamline your marketing strategy and accelerate sales. It also reduces the time and resources that are required to perform tasks such as manual lead scoring, sales pages optimization, and retargeting.
11. Better Business Intelligence
It can take a lot of time to create the perfect algorithm for your business. To improve the accuracy of results, it takes many tests and constant iteration. This can take several months of human effort. Machine learning automates predictive analytics, allowing models to be put into production much faster than traditional business intelligence models (BI). The models learn and adapt as new data is ingested. This feedback loop provides greater performance and accuracy in a shorter time frame.
You can throw away what you know to work. Understanding the intent of consumers means removing KPIs from performance indicators and identifying variables that are known to be indicators of performance. It has been repeated to me repeatedly that I should let go of the things I know to be true. AI doesn’t have preconceived biases, so it will discover patterns in the events that correspond to business outcomes. It can either confirm what we know or uncover entirely new results that cannot be found by human analysis.
Traditional business intelligence does have its benefits. This practice has its limitations in terms of its ability to adapt and scale with new norms in an environment that is more competitive, faster, and requires accuracy. We may also be blinded by our own blindspots, allowing traditional BI to remain the best solution. We have a tendency not to see critical insights in an AI framework.
Also read: The Importance of UX Design for Data Driven Online Businesses
12. Improved User Experience
Marketers must balance high conversion rates and sales with user-friendly websites and apps. This is a constant challenge. Yet, UX can be a win-win for both the user and the marketer. Because customers will be more inclined to return to your brand if they have a positive experience with your front-facing tech.
AI can automatically adapt UX to user interactions. This makes UX more adaptable than traditional optimization and testing cycles.
Your organization will be left behind in a world where technology is increasingly used in marketing if it ignores the potential benefits of AI.
Although advanced artificial intelligence may seem daunting, it is extremely user-friendly and can be integrated with existing systems. Today is the best time to explore the world of AI-powered marketing technology.
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