Driving Higher ROI with Twin Fold Use of Intelligent Recommendations and Bidding
The adoption of AI in marketing has been quite the buzz among the marketers for a few years now. The implementation of AI by organizations has been growing steadily too. The number of enterprises using AI in some form has grown by 270% in the past four years, according to the Gartner 2019 CIO survey. In addition, a Forbes report says that the departments prioritizing AI the most are marketing and sales, and stands at 40%.
The growth of AI is mostly attributed to the machine learning module and the speed of adaptation of Machine Learning algorithms. Although these technological improvements have helped marketers and advertisers to create and drive better campaigns, they can do more harm than good at times. This is especially true in the case where the marketers overlook one important aspect of AI: providing a better customer experience.
There are several possible reasons which may lead to a poor user experience despite having robust AI-based tools at one’s exposure. The Machine Learning based algorithms enable the marketer to collect information about their users and allow targeting them with relevant marketing collaterals. However, if not handled properly, the data becomes too overwhelming and leads to a poor understanding of the actual user preferences, leading to poor user experience.
Leveraging AI in marketing can result in a massive impact in terms of growth and improving conversions. However, keeping the balance between the AI-tools and a sound data science practice is crucial to improved user experience.
How Machine Learning Enhances User Experience?
One key expectation of using AI in marketing is to improve the user experience. Providing a great user experience usually starts the moment a consumer comes to your brand with the intent of buying something from you.
The user experience is built over the entire time the users are engaged with you. A positive experience depends on the efficiency of the journey that they take before and after converting. If you are able to enhance the overall purchasing journey of the users, you can generate faster conversions and ultimately better ROI from your marketing activities.
AI helps in improving the user experience by letting you serve relevant ads or marketing collaterals across channels. The Machine Learning algorithms in the AI-based platforms analyze the behavioral pattern of your users according to their online activities. These algorithms have self-learning capabilities and gives insights of users’ journey through the marketing and sales funnel.
The following sections will speak more about how AI improves user engagement. They will also tell you about the evolution of a few Machine Learning algorithms, that would help you to provide a better user engagement, and eventually improve your overall marketing ROI.
The Role of Machine Learning in Improving User Engagement
AI in marketing can provide an immersive ad experience to your users. Moreover, it makes the ads and marketing communication less intrusive for you to trigger relevant communication according to the users’ online behavior and preferences. Additionally, the marketers stand to benefit from the AI application in marketing as it makes their communication more targeted. In other words, AI in marketing platforms help you to choose the best audience segments sending your marketing messages. As your communication is received by the users who are more likely to convert, you can save on advertising dollar and generate a better ROI out of your campaigns
Leveraging AI in marketing helps you to take intelligent and informed decision about your marketing drives. AI platforms provide a bridge for human and machine collaboration. Hence, it is expected that the marketing stack would behave in a way that is more human-like, and therefore can provide a viable solution to the users needs.
The AI platform provides intelligent insights and help you to sort them for creating campaign, optimized for better user engagement. The AI system understands the user behavior and the online activities, and enriches the data for further use and to help the users to make a purchase decision faster.
AI-tools like chatbots are perfect example here. Chatbots are deployed on websites to enhance the user experience by allowing them to have a human-like conversation about the product they want to purchase. Chatbots are constantly deriving past insights about the users, and can make the purchase process faster by showcasing products according to the users preferences and urging them to convert.
Marketing encompasses communication through both programmatic and CRM channels, and you must optimize both to drive a higher ROI. Also, your platform should understand what product to recommend based on user behavior. This is where IntelliRec and IntelliBid brings in the most comprehensive solution for leveraging AI in marketing.
Intellirec and Intellibid: The Twin Towers in Omnichannel Marketing
Marketing and advertising depends on the amount of visibility the products is experiencing. The advertising ecosystem relies heavily on the ad positioning, and subsequently the bidding process for certain products become crucial. Marketing, on the other hand, depends mostly on the CRM tools, and look to garner engagement from users through relevant recommendations according to the interests and preferences of users.
Enters IntelliBid and IntelliRec. Plainly speaking, IntelliBid optimizes your bidding process, while IntelliRec streamlines the recommendations sent to your users. The following sections gives you a walkthrough of the algorithms and help you to understand the unique capabilities of each.
IntelliBid algorithm helps you optimize your bidding process, and the ad budget associated with it. The following example would help you to understand how it is done.
Let’s say your users are interested in certain products on your website and browse through them for checking out the product details. The users are tagged through a tracking code or a cookie, that lets the publisher know your interest in engaging the users with retargeting ads. Thus, the next time the user visit some other website, the publisher recalls your code to ask you for making a quotation for serving ads in the advertising space. Depending on your response, the publisher would host a auction for the ad space, and the most appropriate bid is displayed to the users if you win the auction and pay the bid amount to the publisher.
All these common practices when it comes to CPC advertising. However, they have a few cons too. You need to manually analyze all the variables and bucket combinations to understand if showing the ad would actually be beneficial to you. Moreover, the scaling of parameters associated with the bidding pattern becomes difficult to handle at times, leading to wastage of ad dollars.
This is where, Intellibid puts your bidding process ahead of your competitors by analyzing the data using the user attributes. IntelliBid is capable in analyzing 40+ user attributes and gather data from consumers, product preferences, and publishers to place automated bid at the right time. IntelliBid assigns scores according to the data it collects and bids for users in Ad exchanges, and places the bid more accurately.
Since IntelliBid can work with Big Data, the process becomes scalable according to the size of the audience. Reinforcement learning and constant evolution in understanding the user behavior is taken into consideration too, which let IntelliBid to score above 90% in accuracy.
IntelliRec allows you to implement an array of tasks in your notification campaigns. You can personalize communication with your users by advanced segmentation and customize messages as per the user behaviour in the segments. Additionally, the IntelliRec engine helps you to send product recommendations using a machine learning algorithm that analyses the online behavior of your users and provide them with the product they prefer, making your marketing communication more engaging.
IntelliRec works with dynamic notifications, and is based on the principle of banner personalization. It considers the interest of the people it is served to, and creates more personalized messages according to the target audience. IntelliRec simplifies the recommendation process by taking the current and the past user activities. Along with the “user history”, the algorithm takes “aggregate user behavior” and “client catalog” into consideration to recommend products that are more aligned to convert users.
Adding to the algorithm, features such as product labels and carousel notifications increases the user engagement. Since the traffic distribution and sending of notifications are automated, the algorithm optimizes the chances of users converting. The algorithm is also useful when you are looking to upsell your product, as it helps in promoting products with higher values in the same category, thereby, increasing the overall basket value for your users.
The twin engine of IntelliRec and IntelliBid allows you to target your users according to their preferences. Therefore, the chances of engaging them becomes quite higher, which leads to better conversion rates. Moreover, since the algorithms analyze the user behavior and intent of users in the backend, it helps you to optimize your marketing ROI by controlling the spend of marketing dollars.
Engaging your users with relevant marketing communication about their preferred product is the cornerstone for any successful marketing campaign. IntelliRec helps you with creating marketing communication based on user activity, thus making it highly impactful. Similarly, when you are bidding your ad for gaining maximum visibility, IntelliBid can be very effective. The twin fold working of IntelliRec and IntelliBid helps you to stay relevant with your offers, and optimize your marketing budget too. Also, they help you to plug the ad wastage, and improve the overall marketing ROI. For knowing more about IntelliRec and Intellibid, please get in touch with us at email@example.com.