Personalization is the key factor to drive customer engagement and retention. But, how can you use customer persona to predict what interests your customer? One miscommunication can cut ties permanently with the customer and will have a negative impact on brand value. Research by Parature State of Multichannel Customer Service reveals that “65% of consumers surveyed said they’ve cut ties with a brand over a single poor customer service experience”. AWS Amazon Personalize services come with full AI and machine learning powered solutions, to help businesses drive smart customer satisfaction and engagement with better personalization solutions.
The key to personalization is building a customer persona. by identifying precise user data and extracting intelligence information to understand the user’s interests. This is vital to understand the user. Upon mapping user interests, the customer personalization journey can be planned.
Moreover, customer interests are dynamic and vary over time. So, getting real-time customer satisfaction information in service delivery matters the most. This way, the application can be more dynamic and intelligent enough to define and run the customer personalization journey.
A 5 percent increase in customer retention produces more than a 25 percent increase in profit..."
To increase the personalization rate, it is mandatory for the businesses to devise applications to be proactive enough to understand user choices before the user decision process and make recommendations. So, the timing at which the user is served is the key and will add value to user journey. This way businesses can save users time in getting what they want, thereby increasing the user satisfaction index. This is where AWS Amazon Personalize uses machine learning and artificial intelligence.
AWS Amazon Personalize makes use of machine learning and artificial intelligence algorithms to automate and accelerate the above process to deliver real-time analytics and recommendations based on user demographics. This solution brings in the right balance of accurate data and technology to generate better customer personalization results.
As mentioned by official sources, “Amazon Personalize automates and accelerates the complex machine learning required to build, train, tune, and deploy a personalization model.“
Figure: Amazon Personalize working
Businesses are struggling to get ML/AI capacities into their applications to streamline activities such as mapping user personas, user recommendations, custom-made promotions and displaying search results in accordance to the user's needs. Getting your development team focused on these tasks isn’t easy as these are complex systems and requires investing time, skills and cost.
For most of the SMB’s, including larger enterprises it is not possible to maintain a team of machine learning experts. Amazon Personalize gives developers the entire process with just an Amazon Personalize API (refer above figure). Even developers with no deep AI/ML programming skills, can develop, train, and install the solutions by using AWS Console or AWS SDK. The Amazon Personalize takes the input data then analyzes and classifies it to choose the appropriate algorithm for the personalization model to make recommendations. Simply put, working of Amazon Personalize can be presented as: analyze (data), classify, train, deploy, and make recommendations