Siteline Analytics for Sitecore - Actionable Insights at Scale. Not Just Reports.
Let's Face It - Actionable Insights Are Important
Today's environments are full of best of breed solutions and you need insights that span them all.
The centralized Sitecore analytics solution enables people to make the best possible decisions by:
- Centralizing experience data needed to drive the best possible outcomes for your team
- Applying data mining and AI models to help identify the optimal outcome
- Revealing actionable insights in easy to understand reports and dashboards
Siteline for Sitecore Analytics Key Use Cases
Unified Pipelines Create Superior Results
By bringing together best of breed applications and solutions under a single method of control makes it far easier to unlock value on multiple levels.
Best of Breed Sitecore Analytics Practices
You've wisely chosen the best of breed systems to make the most out of the marketing environment you're in - now it's time to use best practices to bring it all together.
Scale your processes with built in best practices management to enable the organization to get the most out of their data.
Unified no code data management functions that integrates, transforms, orchestrates and models your data in a single easy to use platform.
Best price performance that brings you the efficiencies of a unified platform at the scale of individual services.
Discover How Businesses Benefit with Put It Forward
Successful organizations use the
Put It Forward data platform
Common Data Analytics Platform Use Cases
Personalization At Scale
Problem: While experience data is becoming more granular it is also becoming increasingly fragmented and distributed across the enterprise making it impossible to create personalized end to end interactions.
Solution: Aggregate and unify experience data into a single environment that can be used to create the comprehensive view of the user, product or service being offered.
Result: An up to the moment complete view of the user that can be used to power interactions across your entire business platform.
Platform Cost Reduction
Problem: Data platforms can be expensive and slow when dealing with component solutions from multiple clouds, to data quality, to staging and to production deployments.
Solution: Merge and analyze data from multiple different sources in a single data environment that is equiped with all the tools needed.
Result: A unified data story that can be used to power the entire enterprise and drive high quality decisions at scale by unlocking trapped value.
Data Insights and Predictive
Problem: Real time insights that represent cross channel, system and product events are impossible without integrated algorithms that can reach into the underlying sources.
Solution: Trained models and algorithms that see into the underlying systems in parallel to aggregated data within the platform allow you to create insights that span the end to end data stack.
Result: Data values are unlocked for all participants from those on the frontline to the backoffice and support. Now you can expose your insights to anyone in the organization.
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Learn How To Achieve Success with AI Tools
How Professionals Identify The Best 'New' Customer
Read how to increase revenue with AI and predict customer preferences and buying patterns. Easily understand what the customer wants.
How Predictive Customer Lifetime Value Drives Revenue
Understand how to use predictive customer lifetime value to gather historical data, get more sales, and increase customer retention.
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Understand Your Data Context - Why Choose Put It Forward?
Automation capabilities, security, governance, monitoring, and explainability
No-code predictive model building, AI for customer engagement
Easily ingest, prep, and versioning any form of data
Supports multi-cloud deployment scenarios
Supports the full ML lifecycle tools
Management from multiple clouds, SaaS, applications, and services
Frequently Asked Questions about predictive AI
There are multiple AI tools for data analytics, visualization, and monitoring. With their use, organizations can obtain cross-platform insights and make more accurate executive decisions driving revenue to the organization.
AI-based data insights software by Put It Forward will help business owners and employees analyze high volumes of data faster, identify customers' preferences and needs, and predict their next step to engage effectively.
Predictive AI is a type of artificial intelligence that is used to make predictions about future events and trends.
Artificial intelligence predictive analysis systems are trained on historical data in order to learn how to make predictions about future events. With the use of the solution by Put It Forward, business leaders can make accurate AI revenue forecasts, identify new opportunities, and increase the quality of their decisions using actionable insights.
Predictive analytics is a field of data analytics that uses historical data and innovative techniques to forecast future events and conduct advanced data analysis.
Predictive analytics uses a variety of data sources, including financial, customer, and behavioral data. Predictive analytics techniques include regression analysis, time series analysis, machine learning, and artificial intelligence software.
Predictive no-code data analytics can be used to forecast a variety of events, including customer behavior, product demand, or financial market trends. It improves decision-making, by providing organizations with better information about future events.
What’s the difference between artificial intelligence and predictive analytics? Predictive analytics is a branch of AI that deals with making predictions based on data. AI, on the other hand, is a much broader term that covers a wide range of technologies, including machine learning, natural language processing, and robotics.
There are a few different ways of using predictive AI for marketing. One way is to use it to predict what customers are likely to want or need in the future, and then create marketing campaigns that target those needs.
Another way is to use AI-based market prediction to segment customers into different groups so that marketing efforts can be better targeted. Moreover, predictive AI for marketing can be used to personalize messages for each individual customer based on their predicted behavior, and perform AI revenue forecast.