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Artificial Intelligence in Retail - use cases

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Artificial Intelligence in Retail - use cases

Machine Learning can support Retail companies with supporting their operations, improving bottom lines through gaining competitive advantages, reducing expenses and improving efficiency. They can optimize all areas of their businesses, starting from risk analysis to dynamic pricing, to make data-driven decisions that lead to increased profitability.

1) CLAIM DEVELOPMENT MODELING
Machine Learning allows retail companies to predict the ultimate claim amount based on its characteristics.
PROBLEM:
The amount of a claim can vary between the insurance claim’s initial filling and the full payment. It is important to predict the final claim amount, as it makes a significant impact on financial statements.
SOLUTION:
Our solutions, like Pattern Finder and the Information Extraction System, give you accurate tools for predictions that lead to a better understanding of how much a claim will cost. You can have confidence in how much to reserve for Incurred But Not Reported Loss Amounts.
WHY LONSLEY:
We make your business simple and effective with Machine Learning-based predictions, at the time of filling, the ultimate claim based on the characteristics. We also extract the text features and correlate it with the different parameters to give you true insights about claim adjustment. You don't have to be an AI expert - that’s our job.

2) CONVERSION MODELING
With the predictions of conversion from a quote to a sale, retail companies can optimize their pricing and marketing actions to make better, data-driven business decisions.
PROBLEM:
Retail businesses are looking to gain insights into conversion rates based on new pricing plans. How do you achieve higher profitability without driving your existing customers away? You need to predict the likelihood of converting a quote to a sale.
SOLUTION:
Our cutting edge solutions with extremely accurate algorithms, like the Data Driven Sales Optimization System, can predict the likelihood of a quote becoming a sale. Using this information, you can easily optimize your spending, especially expenditures on marketing to reach out to many more customers that may be more likely to buy, without doing anything to push your customers away. Our solutions also project the retention rate to allow you to give valuable information to shareholders and prepare the company for the future.
WHY LONSLEY:
We use Machine Learning to give you the most accurate information about predicted conversion rates to help you make the proper pricing and marketing decisions, get insights about what your customers want and increase conversion rates. You don't have to be an AI expert - that’s our job.

3) DIRECT MARKETING
To build a successful business in retail, the key is to maximize ROI. You can do this by boosting marketing response rates and minimizing misdirected communication. Current state-of-the-art algorithms give the best results, but they also require a specific, deep domain (subject-matter) expertise in Machine Learning.
PROBLEM:
Marketing to prospects is expensive and is going to be more difficult with the coming of GDPR regulations. There is no point in using default schemas for direct emails and telemarketing, as it is not going to help you target the right customers. Incorrect targeting hurts your brand and makes your prospects feel like they are being spammed, resulting in low response rates that lead to a high cost-per-lead.
SOLUTION:
Our cutting edge algorithms included in the Data-Driven Sales Optimization System can deliver information about which people are most likely to purchase your product or service, yielding higher ROI. To achieve your goals, maintain a favorable image of your company with targeted communication to save time and money.
WHY LONSLEY:
Our Machine Learning systems will make your marketing campaigns more effective. You don't have to be an AI expert - that’s our job.

4) FRAUDULENT CLAIM MODELING
Retail companies can have a lot of money lost due to fraudulent claims. Reduction of fraudulent payouts helps your business save money and deliver your customers a great customer experience.
PROBLEM:
Fraudulent claims are costly. Even if they are expensive, it is even more expensive to check every single claim for fraud and takes a lot of time. Investigation of innocent customers leads to a very poor customer experience, pushing clients to leave your business.
SOLUTION:
Efficient and extremely accurate predictive models that identify likely fraudulent activities. This allows you to investigate only those incidents that likely require it. It results in a better utilization of your resources - they are used to bring the greatest return on the investigation. We allow you to build a better customer experience and protect customers at the same time.
WHY LONSLEY:
Our systems automate predictions of the likelihood that a specific claim is fraudulent or not. You don't have to be an AI expert - that’s our job.

5) SERVICES/PRODUCTS PRICING
If you want to stay at the top of the retail industry and have a profitable business, you have to implement a pricing policy. To do this, you need to have a highly accurate predictive models.
PROBLEM:
Many retail companies are seeing lower sales results. Due to the current situation on the market, people can compare many companies instantly, mostly choosing the lowest price. Smaller companies are being exposed in the areas where they mispriced to make a sale. Mostly, the low price makes the business underpriced relative to the risk, which results in costing companies huge amounts of money.
SOLUTION:
Using the algorithms we provide with Data Driven Sales Optimization System, you can be totally confident in the prices you charge. We automate the process of exploration of cost versus risk to increase your profitability - to make sure any risk you consider taking on is priced appropriately.
WHY LONSLEY:
We build efficient Machine Learning models and select the best ones to help you save significant amounts of money and assure you that the final result is the best for you and your business. You don't have to be an AI expert - that’s our job.

Wednesday, 13 March 2019