The market for affiliate marketing is expected to reach $8.2 billion by 2022. AI is making it easier than ever to succeed in this growing field.
The application of Artificial intelligence and Business Intelligence in affiliate marketing has been actively discussed for quite a time. No wonder, more or less but the majority of marketers have already applied them both at their campaigns. Companies like Propel Media are using machine learning to deliver ads to customers that are most likely to convert. Bloggers are using AI to better identify target customers and create the right content for them.
And as they say, taste once and you will not be able to refuse another time! And there is no need to! With every year, AI technologies only become stronger and introduce new features. They automate a large amount of work and help manage marketers’ work properly. And as marketers quickly get used to innovations that significantly improve their work, they tend to generalize AI and BI. The lack of nuance can cause them to mislead themselves and others in what is what.
Chief Marketer talked about some of the ways that AI is changing the field of affiliate marketing. You can review their content for more details, but we have summarized a lot of the concepts here.
AI is the Key to Driving Growth in Affiliate Marketing
Therefore, in the following paragraphs, we would dive into the details of AI and BI. We will clarify the differences between them and showcase how AI and BI work alone and together, and how their synergy can make ad campaigns stronger.
Both AI and BI are deployed by collecting and analyzing large volumes of data. They both are aimed at easing the working process, releasing from manual work, speeding up the decision-making process, and making it more data-driven. Somewhat similar definitions might be misleading. Two word-combinations, both consist of two words and have “intelligence” as a common one. When in fact, it is not the same intelligence. In AI it refers to computer intelligence, while in BI it is about smart decision-making in business influenced by data analysis and visualization.
Though there is an inevitable overlap, these two are not the same. Let’s once and for all draw a distinction between these two definitions.
Business Intelligence
The aim behind BI is to streamline the process of collecting, organizing, and analyzing data. BI tools allow companies to significantly improve the quality of the data they collect and its coherence. They can turn mountains of data from absolutely puzzling mess to a pretty coherent picture. Ideally, this data extracted by BI should provide marketers with information on advertisement trends, audience engagement with creatives, and resource allocation. Companies’ data can indicate the viability of the current strategy and help in the planning of future growth hacking actions. In this way, BI carries out its mission – to simplify marketers’ work with data.
Artificial Intelligence
AI represents the ability of a machine or a computer program to think and learn. In plain language, it means that AI explores the use of computer systems to imitate various patterns of human behavior. Thus, when applied to affiliate marketing, instead of the constant human presence, AI can decide how to update the program setting and which traffic to send to which offer.
The use of BI in affiliate marketing
Over the course of running ad campaigns, marketers collect high volumes of all-encompassing data that they further translate into strategies for future ad campaigns. The problem that comes along with this amount of data is its storage. For most companies, it is stored in massive spreadsheets or servers, scattered across different sources. To analyze the full campaign’s performance, as a first step, marketers need to pull all this data from different sources into a single view. And for this, they need BI integration tools.
As an example, let’s have a look at Data Fusion. Data Fusion is a BI integration service created by Affise performance marketing platform, that transfers all the data from its platform to customers AWS and Google accounts.
It works as follows: Affise users integrate Data Fusion, and once the integration is established, Affise transfers reams of users’ data to their AWS and Google accounts. In this way, users get all their data on their advertising campaigns in one place. And as the next step, the data is sent to such leading-edge BI tools, as Google Data Studio, Power BI, Oracle BI, Tableau, etc., where data is visualized in multiple easy-to-understand graphs and reports.
The use of AI in affiliate marketing
AI helps to process a massive amount of data, and using the machine learning approach detects advantageous behavior patterns. In affiliate marketing, AI is often used to automate traffic management, validate broken and expired links, keep numerous offers under one link, and with ML methodology distribute relevant traffic on more beneficial offers.
Obviously, all affiliates want to manage the quality of their traffic smartly to increase their ROI subsequently. An essential help in achieving this is provided with the CR optimization tool, which is available on most affiliate marketing platforms. The tool checks data compliance with the preset CR restrictions, based on that filters traffic and sends it to the most likely to be converted offers.
Also, AI is good at preventing fraud in affiliate campaigns. In comparison to the other option, rules-based methodology, the Machine Learning approach is much more reliable when it comes to tackling fraudulent online attacks in affiliate campaigns. ML algorithms analyze dozens of metrics and connections between them and consequently stop fraudulent traffic. Take an example of a click-level fraud prevention tool. It is developed to eliminate fraud attacks by filtering VPN, non-earmarked traffic from bots and proxies, etc. The tool runs fraud checking in real-time – ensuring the high quality of detecting and blocking fraudulent traffic before it can hurt the destination website.
The synergy of BI and AI
BI and AI are self-contained but complementary. If used separately, they don’t tap the full potential. BI helps companies to organize the massive amounts of data they own, but neat visualizations and dashboards may not be enough. You may have a nice picture, but BI tools alone are not designed to provide precise guidelines on how to use this for decision-making.
The overlap of AI and BI is not an exchangeability of each other, but rather a beneficial supplement. By supplementing BI with AI, marketers can turn a vast amount of neat graphics into a concrete roadmap for their business. In this way, they can automatically analyze the old data, compare with the new one, and on this basis, adjust settings and create new features. In other words, you will get direct actions derived from your analytics.
Creating a Successful Affiliate Model with AI
Here is some advice. Keep implementing the best of AI automation features – optimize the traffic to reach the targeted audience, automate the tedious workflow, continuously validate “living status” of links, prevent your campaigns from fraud. And at the same time, don’t be scared of BI with Big data. The future of AI and BI depends on each other; together they have the power to revolutionize the usual way of doing business.
