Find the best prospects. Increase cross-sell and up-sell. Choose content and media that convert. Squark intrinsically sees patterns invisible to conventional data analysis tools.
Identify high-overhead customers. Optimize support resources. Stop ad spend on non-performers. Reduce overhead with smoother customer journeys. Squark finds answers that help your bottom line.
Rank your opportunities by win-loss risk. Alert on process problems that hurt revenue or image. Find factors that contribute to customer satisfaction and churn. Replace guesswork with explainable predictions.
Crush revenue targets. Win market share. Close opportunities with the best prospects. Avoid time wasted on dead ends. See clearly what others miss. Spot trends and make moves before others know what happened.
If you could predict the future, what would you want to know?
Identify your use-cases and business questions (Squark can help!) .
Login to get started with clicks and no-code required.
Click to connect with no friction.
Squark is a SaaS application with no implementation overhead. Monthly and annual plans are available to fit your budget.
Instant predictions.
Click to start Squark’s no-code predictive analytics process.
Squark automatically prepares your data and applies machine learning to create the best predictive model dynamically to your data. And then automatically creates accurate, explainable AI predictions in minutes.
Squark transforms the way you work by creating the best predictive model for you and automatically applying it to predict on your data.
It’s that simple to get the best predictions in minutes. Accurate predictive analytics are now fast enough to automate today’s customer experiences
Predictions in minutes with clicks, not code. AI accessible to all, with no data scientists needed.
Squark® empowers companies to create predictions from the data they already have at their fingertips – in spreadsheets to Google Sheets. Use your data from Adobe, Amazon S3, Azure, Domo, Segment, Snowflake, Salesforce and more.
Easily familiar like Excel or Google Analytics, Squark’s no-code automation encapsulates the entire AI and machine learning process into clicks, doing the work of a team of data scientists. Squark is no code data science. Some call it “no code predictive analytics” or “no code analytics.” Regardless Squark makes it simple to connect data about your customers and other entities (like behaviors, events, transactions, products, campaigns, and so on).
Simply connect your data to Squark to get instant predictions built from today’s leading AI algorithms dynamically applied to your data.
Squark automates data prep, feature engineering, model creation and validation, prediction, explainability/transparency, and MLOps into one no-code platform.
Simply click to get the best predictive results to drive your yield and turn your data into dollars.
Predict Customer Response and Outcomes
Example Use Cases:
Will the customer buy?
Will the customer have a high lifetime value?
Will the contact become a marketing qualified lead?
Will the lead respond to this marketing campaign?
Will the customer churn?
Determine actions to take now to win later
Example Use Cases:
What offer should I make next?
What is the probability of response to offers?
Will products will customers buy next?
How should I segment my customers?
How should I personalize the experience?
Predict any single value
Example Use Cases:
What will be the lifetime value per customer?
What price should I offer to each customer?
What will by cost of customer acquisition be?
How many transactions will occur next week?
What will my conversion rate be next month?
Forecast any series of numbers over time
Example Use Cases:
What will sales be next year?
How many deals will close daily this year?
How will my costs change by day next year?
How will my risk change by month in 5 years?
What will the price be each minute next hour?
Determine “why” predictions occur and the drivers in the data
Example Use Cases:
What marketing touches contribute to conversion?
What parts of the customer journey cause sales?
What data impacts the forecast?
What specific data is contributing to this outcome?
What data is most important?
Explain models and understand the bias in your data
Example Use Cases:
What specific values in my data caused the sale?
How does each data element contribute to outcomes?
What values are important to consider?
What data is causing bias in my results?
Why does the model predict what it
predicts?
