A Data Science platform is enabled to improvise the way you work. It is a way to wrangle data and turn every function of your organization into a high performing unit, capable of pivoting and scaling without missing a beat. The right one is transformative to your work.
If you’re spending a lot of time on basic operations, it might be time to adopt a platform. Supply Chain Leaders need to overcome the following challenges to improve their Customer Experience
Our Solutions on Google Cloud help arrest these challenges, thereby improving Customer Experience
Pluto7 offers a collection of services and solutions that comprises 4 different components for a plethora of use cases. The bundle can be chosen as per the business use case or can be tailored depending upon your requirements.
Adopting the bundle offering leads to enablement of GCP Data Science Platform with one or more priority use cases. The same platform can be extended further to incorporate the state of the art solutions for enhancing the customer experience and improving the business profitability.
A Demand Planning solution focuses on augmenting the existing engine. It creates demand forecasts for the existing merchandise targeting primarily on efficient supply chain management. The solution can predict demands by fulfillment categories as well for further improvising the logistics and resources at hand.
Demand forecasting is the need of the hour for organisations. At Pluto7, we have our team of experts to customise a bundle just for your business needs.
Machine learning models are built to maintain the asset lifetime, operational efficiency and uptime by leveraging history data. Predictive maintenance maximizes the use of the company’s resources by detecting the anomalies and providing early warnings.
For Predictive Maintenance to work with machine learning following components are necessary:
To start your Preventive Maintenance journey and build a data set to explore your data, Talk to our experts now.
Inventory management has posed critical challenges in front of the business leaders specifically in the pandemic times.
Forecasting the product demand is one of the core challenges for businesses. The main question is, how much stock of an item should a company/business keep to meet the demands? Forecasting is a key enabler for a better customer experience through the reduction of out-of-stock situations, and for lower costs due to better planned inventory.
The use of artificial intelligence in managing inventory is a vital process for businesses. Careful evaluation of internal and external factors through better planning can improve the status of inventory by building ML models.
Kickstart your inventory management journey leveraging the ML models.
Supplier ranking systems consist of quality, delivery and service responsiveness. The supplier performance with improved communication has the ability to grow your business by improving overall competence in the market.
To be able to deliver the goods on the scheduled date, a supplier needs to be ready and for this he requires a predefined ML model with the ability to forecast.Service quality is the most important criteria for the supplier. Pluto7’s Supplier ML can help deliver the correct quality of products in time.
To penetrate the customer centric market, it is vital to understand the Customer’s Lifetime Value (CLV). It can be predicted by the ML models that take into consideration the transaction history of the existing customers and the touch points from multiple other data sources available. Further, these ML models are capable enough to predict the CLV for the new customers by comparing the behaviour posed by them with the existing customers
If your business is driven by increasing Customer Lifetime Value & Selling more content then Pluto7 is the right space for you.
Talk to our AI/ML experts to get started!
Personalisation is carried out for customer benefits in order to drill down to the desired content. The more personalised and curated services you have, the larger the customer base.
ML models can easily study the data sets that you feed in the model and get a desired outcome to enhance your customer experience.
Pluto7 has build ready to deploy ML models to get started with, which can be tailored as per your requirements.
Supply forecasting helps in making an estimation of supply of human resources taking into consideration the analysis of current human resources inventory and future availability. This is done by analysing the trend of the organization for example, head count, future availability of resources that might be required. The trend analysis involves the study of external factors and analysis of data.
The solution helps predict the likelihood of a certain type of customer purchasing behavior, like whether a customer that is browsing your website is likely to buy something. It helps marketers optimize anything from email send frequency, to sales staff time, to money, including discounts and also assists sales team in spending most of the time with the prospects having highest likelihood to become buyers.
By using purchase prediction it is possible to create a Conversion Prediction model (analysis) that uses site purchase data from Google Analytics 360 (data source) for identifying high/low propensity segments to push back to GA360 (activation channel).
With AI going mainstream, dynamic pricing is something that is common even for all e-tailers and retailers. E-commerce generates huge data that can be handled more efficiently by ML models than by humans.
GCP can be leveraged to achieve secure, serverless, scalable price decision applications that can be adjusted to your product’s price in response to real-time supply and demand using ML/AI.
Switch to Pluto7’s fully automated process with advanced AI capabilities. Talk to our AI/ML experts to get your automated ML model and get started with your FREE TRIAL!
Machine Learning models are capable of profiling the best performing customer segments automatically.This can be performed in a supervised or in an unsupervised manner. Supervised machine learning includes a set of rules and adjusts to the operations to yield output while the unsupervised ML allows AI to build new data sets and begin finding the patterns on its own.
With Customer segmentation you can achieve the following;
Pluto7 helps customers build particular solutions that can help you enhance your customer relationship and yield best results to your benefits.
How about getting to know everything about your customers? What do they need? What do they think? Nearly all would get you to the space where acquiring a particular customer will become a lot easier than it is now!
Incorporating AI and Machine Learning capabilities into modern software solutions is paving the way for intelligent automation. While working with Data Silos it is very important to understand how to segment that data and use it for your benefit.
Pluto7 can help you segregate your data and build tailored ML models that are a perfect fit for your business.
Many of the analytics tasks on ML platforms are semi or fully automated but with self-service ML the best you get is that training and deploying of the ML model is automated so that the business user can fully concentrate on the data.
AutoML consists of data acquisition and prediction. It is a highly scalable analysis tool helping the organization gain better insights of their data.
Pluto7’s machine learning models help you get access to an increasing number of self-service ML models that are ready to use right away.
It allows the customer to gain an overview of the wider public opinion behind certain issues and analyze customer service interactions in order to adjust marketing messages by leveraging:
Accurate segmentation is one of the cornerstones of an effective marketing technique. . Segmenting or dividing your audience into groups means that you can target messages to customers with similar characteristics and needs. Product segmentation helps create subsets of information based on a range of psychographic or behavioural criteria by augmenting processes using machine learning (ML) and artificial intelligence (AI).