There are two kinds of people who are at the center of ECommerce company's operations. They are technology experts and those who are good at the domain of the particular ECommerce line of business. As ECommerce businesses evolved over the last decade ECommerce companies started seeing the value of data. To leverage the value of data to its full potential ECommerce, companies need to have data science experts on their team. Data scientists are expensive and also take more time to demonstrate results than acceptable in a typical ECommerce SMB culture. So the critical question has been how to adopt data-driven decision making in ECommerce without having the data science skillset?
The answer is right there within the realm of artificial intelligence. If AI is dominant, then can it not build the intelligence to build machine learning models with little to no help from data scientists? This argument leads to the advent of AI-driven AI or AI to do AI or self-learning ML.
Who needs AI in ECommerce?
The answer is every ECommerce company. However, we could be a bit more precise in terms of who can benefit the most from AI in ECommerce. Take a look at the following list:
- Any ECommerce company that is selling more than one product or services online
- They have at least 100+ orders every month
- They have been offering special discounts and combo-deals, based on assumptions
- The highest proportion of their monthly orders is from first-time customers and very low repeat customer orders
- They are only guessing which products to show as recommended products for upselling and cross-selling
- Those who are product owners, and have been finding it difficult to forecast the demand precisely
Companies that have one or more of these attributes are qualified to leverage the power of AI.
What is AI-driven AI?
"AI-driven AI" signifies that software can build machine learning apps for your data without needing an expert. In essence, you have an online platform to upload your data, select the AI use case, and get your output. AI-driven AI platform has pre-planted datasets, and ready apps around most well known AI use cases, viz. product recommendations, customer churn prediction, demand forecasting. Your business or engineering team members who understand the domain can begin experimenting with the data using the AI-driven AI platform. Typical steps to use an AI-driven AI platform are as follows:
- Choose the AI use-case or application
- Choose the dataset either from the readily uploaded sample or upload your data
- Map a data field to specific input action or desired output based on domain knowledge (feature engineering)
- Train the inbuilt models on the platform
- Observe the model training output, evaluate the output quality based on readily provided indicators on the platform. Re-train the model if needed to increase accuracy with update dataset or change in algorithm
- Try the trained model to experiment on current data and get the required business insights
- Create an API or host a batch mode app on the cloud so that you can push the insights straight into your business application
To get acquainted with AI-driven AI platform, you need to try out and master a few inbuilt AI applications on the platform. Once you are comfortable using it, you can go ahead and bring in your dataset and experiment upon it.
Benefits of AI-Driven AI to ECommerce SMBs?
One of the most critical benefits of AI in ECommerce is the incremental business; it is also the metric to evaluate the performance of your AI project. Here is a list of benefits for ECommerce using AI-driven AI platform:
- You begin experimenting with your data at much early stage
- You do not need extravagant budgets to adopt AI and ML
- You can expect to use outcomes from AI experiments within 2 weeks
- You don't need to hire exotic data science team to adopt AI
- Your engineering team gets upgraded to an AI-driven engineering team
- AI and ML starts becoming part of your ECommerce business design
There is no right time or wrong time to switch to AI and ML-driven business in ECommerce. AI-driven AI is about getting AI on board quickly so that your business data works for you without it turning into dark data.