A survey found that 96 percent of senior marketers spend almost one workday a week trying to improve their data analysis processes, but still find it challenging to do so. This is just one of many examples of how marketing professionals can use AI to their advantage.
Following are some ways artificial intelligence is redefining digital marketing today.
1. Predictive Marketing and Improved UX
AI can be used to collect customer analytics on a much larger and more efficient scale. This data can then be used to provide users with an improved and personalized user experience.
One example of how the UX can be improved with AI is by employing predictive marketing. By analyzing a customer’s previous search and/or purchase history, you can get an idea of what kinds of things they would be interested in.
By making targeted recommendations to your customers based on that data, you can help them find what they are looking for quickly and increase your sales and ROI.
Netflix is a good example of how this works. They’ll recommend films to their customers based on their previous viewing history. In fact, Netflix saved $1 billion in 2017 by keeping customers satisfied by showing them personalized recommendations.
Amazon and eBay are good examples of ecommerce sites that give their customers personalized recommendations on-site and via email.
If you operate a blog or content site, you can show recommended content to your visitors based on their previous reading history. Quora, a popular Q&A site, is a good example of this.
2. Multi-Channel Analytics
Another way machine learning can be used to improve your analytics process is by collecting and curating analytics from multiple channels.
Instead of focusing on just Google Analytics, Facebook Analytics or other data provided by a single platform or service, AI can combine all of them to give you a much more complete picture of who your customers are and what they are looking for.
3. Email Marketing Analytics
Predictive marketing can be applied to your email marketing strategy as well. You can send personalized product recommendations based on customer’s previous search history.
Another way AI can improve your email marketing campaigns is by analyzing your email marketing data to help you figure out things such as when the best times to send your emails are and where in your emails you should place your links.
This can help you improve your open and click-through rates.
4. Content Creation and Curation
AI can be used to both create and curate content. Machine learning can be used to create web content and news updates for consumers.
During the 2016 Rio Olympics and the 2016 Presidential Election, the Washington Post used Heliograf, their in-house developed AI, to create short news content updates about games and scores.
AI can also be sued to curate content from multiple sources. This content can either be used for research purposes or for a content curation service for your customers.
5. Improved Warehouse Management
One of the many benefits machine learning can provide ecommerce businesses is by improving their order handling and shipping processes. Inventory & stock management is complex and time consuming.
Amazon, for example, has reduced the click-to-ship time to merely 15 minutes by using AI systems in their warehouses.
6. Sales Forecasting
Another way machine learning can be used in ecommerce is by helping you forecast consumer demand for certain products.
By analyzing previous sales history over time and taking into account current trends, AI can help you figure out how much of a product to stock up on.
This will help you avoid running out of stock on popular items and not waste money by overstocking.
7. Speech Recognition
AI can be used for voice recognition purposes, allowing users to conduct voice searches on any site.
Siri is one of the most well-known examples of how voice recognition can be used to improve the customer experience.
However, if you operate an e-commerce site, you can use machine learning to find the best matches for consumers who are using voice searches on your site.
8. Image Recognition
Image recognition has many benefits beyond security software that uses biometric face recognition. As with voice recognition, image recognition can be used to help consumers find products they are looking for.
How can ecommerce businesses take advantage of this?
Let’s say a consumer sees a product in a store or in a friend’s house. They may not know the name of the product, which brand produced it, or what it is called.
By snapping an image of the product with their smartphone, they can then upload it online to a search engine. AI can then identify the product and/or brand and help users find the product on your e-commerce site.
AI has plentiful to offer, not only to e-commerce but to various other verticals too. Online business presence essentially needs digital marketing to survive today. Isn’t it?
9. Dynamic Pricing
Having a fixed price for every product is standard practice. However, that may not be the most optimal pricing system.
Machine learning technology can be used to create a dynamic pricing algorithm.
For example, you may want to charge different prices for the same product based on the season, on the customer’s location or country, on their previous purchasing history, or on your available stock count.
This can help you keep your prices adjusted to effectively boost your ROI.
10. Programmatic Advertising
Programmatic advertising refers to a system that uses machine learning to automatically buy ad space and place ads on different websites. This cuts out the need for manual searches and price negotiations.
AI can help match your ads with ad spaces on blogs and other sites that cover similar topics or have the same target audience as yours.
There are many advertising networks that do this already; a good example is Google’s display network.
11. Lead Generation and Targeting
Machine learning can help you focus on the right leads to getting better conversion rates. By analyzing data that you already know about existing leads, AI can help you pinpoint which leads are more likely to lead to a conversion.
This can help you save time and money by getting a higher conversion rate and a higher return on investment.
12. Customer Service
Of course, one of the big ways AI can be used in marketing is by improving customer service. Chatbots are a great example of this.
Bots can be used to help answer customers’ problems and help them find appropriate solutions. They can also help new customers find products that they are looking for.
Companies such as Lyft and Starbucks allow customers to place orders via online chat. Whole Foods has a Facebook Messenger bot to help customers find recipes.
They can also be used when creating surveys. They can ask customers stacked questions based on previous answers to help you figure out which areas you can improve on.
It is estimated that chatbots will power 85 percent of customer interactions by 2020.
13. Semantic Search Results
Besides improving search results by allowing users to search via voice commands or image uploads, AI is also changing SEO through semantic search results.
Semantic search refers to how machine learning can help improve search engine results by taking into account natural language and the context of keywords in a search term to determine the user’s true intent.
As search engines start to incorporate machine learning more and more, it’s more important than ever to make sure you are producing natural high-quality content and not simply stuffing your articles with keywords.
Wrapping It Up
Machine learning is shaping how digital marketing works. Make sure to take advantage of the benefits of AI in marketing so that you continue to move ahead in your business endeavors.