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Using Artificial Intelligence To Predict Purchase Intent

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Using Artificial Intelligence To Predict Purchase Intent


The use of AI in marketing allows businesses to understand customer demand for their products and their willingness to purchase them.

Predicting the purchase intent of anonymous visitors from various sources can be a daunting task for your business. Earlier, businesses would gauge customer interest in their products based on factors such as past demand, prices, and rival performance. Today, those factors are still relevant, in addition to a few more such as behavioral trends, reciprocity and product scarcity in the market. Such factors create huge reserves of customer data that need to be scanned and analyzed to get an idea about purchase intent. AI is the perfect tool to find patterns from big data before using them to create marketing and product promotional strategies. As we know, the combination of AI in marketing already has several applications today. Tools such as AI, machine learning, computer vision, and Natural Language Processing (NLP) allow you to go through thousands of data points online to understand each individual’s behavior. Unlike humans, AI can evaluate thousands of data points before carrying out a comparative analysis between the number of possible permutations and the billions of known outcomes. AI algorithms are trained with millions of datasets to predict buying intent in real-time based on such factors. Here are some of the ways in which AI goes about the purchase intent prediction process:

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Identifying Customer Pain Points

Pain points are specific problems your prospective customers are facing with regards to your products in the marketplace. Detecting these points allows your business to know the specific aspects of your product, marketing strategies, or other factors that you will have to modify as per customer requirements. Identification of pain points before addressing them allows you to understand how to purchase intent works for specific products and how you can increase it. Pain points are assessed by conducting qualitative market research and feedback analysis, which can be optimized with the help of AI.

Data can be collected from customers in the form of the voice of customer analysis, surveys, purchase ratings, social media, and others. Customer feedback analysis tools enable you to integrate them with your CRM systems. Once this arrangement funnels in information related to customer interactions, customer satisfaction index, data generated from chatbot interactions with customers, and other similar details, you can use AI to get closer to predicting your customers’ purchase intent by analyzing this data. The AI-enabled prediction of purchase intent using pain points is useful in scenarios where you have information available in the form of market research data and customer feedback. However, how can you predict purchase intent for anonymous visitors on your site?

Predicting Intent from Interest Signals

When direct information is not available, your AI algorithms can collect data from other sources. Generally, visual content consumption is a powerful indicator of purchase intent. There are several third-party service providers who collect user behavioral activity data to understand the factors that drive purchase intent. From such data, AI can forecast the purchase intent for your products by using a few signals, which include:

  1. Number of consumers who visited your website
  2. Time spent on your online page
  3. Scroll Speed
  4. Types of products viewed and
  5. Time spent seeing each product

Predicting the purchase intent of your customers and others is challenging and full of guesswork. Using AI in marketing for the task reduces the guesswork and makes the process more data-driven and the predictions accurate.



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Storbritanniens största hälsoforskningsprogram väljer Microsoft Cloud

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A variety of pills.


The UK’s largest ever hälsa research programme, Our Future Health, which aims to create one of the most detailed pictures there has ever been of people’s health, is to use the Microsoft Cloud to securely store the huge amounts of data needed for the programme.

Our Future Health, a collaboration between the private, charity and public sectors – including the NHS – is building a community of five million volunteers from around the UK, who will give their permission to share health and health-related information about themselves with the aim of developing new ways to prevent, detect and treat diseases.

The programme will look at some of the leading causes of death and serious illness in the UK, including dementia, cancer, diabetes, heart disease, arthritis and stroke.

Our Future Health has now chosen Microsoft’s Azure cloud platform to enable the information collected from the volunteers to be processed for research purposes, and underpin websites and apps used by medical teams.

All of this will be contained in a Trusted Research Environment (TRE) provided by DNAnexus, which will sit in a UK Azure region. The TRE allows researchers to securely access and analyse data using a variety of bioinformatics and biomedical research tools, including genomic analysis.

DNAnexus and Microsoft will work together, however as with any project of this nature, Microsoft and DNAnexus will not have access to any of the data in the programme itself. The information will be de-identified, encrypted, stored and managed securely in the UK, in compliance with all applicable data protection laws and UK government policies for data protection.

Andrew Roddam, Chief Executive of Our Future Health, said: “We’re delighted that Microsoft will be working with us as a key technology partner and providing our cloud services. This will be an integral part of Our Future Health, underpinning so many important systems that are essential to the running of the programme and ultimately helping to create one of the most detailed pictures we’ve ever had of people’s health.”

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Volunteers who join the programme, who will be aged over 18 and truly reflect the diversity of the UK population, will donate a small sample of blood, so researchers can study DNA information and biomarkers, fill in questionnaires about their health and lifestyles, and give permission for Our Future Health to securely link to their health records.

Doing this may hold the key to huge numbers of discoveries, such as:
• New signals that could be used to detect diseases much earlier than is currently possible, leading to new or improved screening and prevention programmes and earlier treatment
• New ways to predict with better accuracy who is at higher risk of diseases and would benefit from faster access to screening and prevention interventions
• More targeted or personalised treatments, tools and technologies to delay the onset of disease, or change the course of disease progression; to reduce disease risks; and more targeted ways to investigate diseases for people at higher risk.

Jacob West, MD of Healthcare and Life Sciences at Microsoft UK, said: “Healthcare teams across the world trust the Microsoft Cloud to deliver better experiences, insights and care, while managing and protecting health and personal data. Microsoft is proud to support Our Future Health’s work, which will provide research teams with a unique view into some of the most common and life-changing diseases that people face.”

The partnership with Our Future Health is the latest example of Microsoft’s work to support healthcare, biomedical research, precision medicine initiatives and clinical collaboration. In 2020, the NHS rolled out Microsoft 365 to all eligible organisations in England, including 1.2 million staff; large NHS trusts in Leeds and Birmingham are unlocking innovation and collaboration by moving to the Azure cloud; while two NHS surgeons in Northumbria are exploring how Microsoft AI can help reduce waiting times, support recommendations from healthcare teams and provide patients with better information so they can make more informed decisions about their own care.

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