This best practice is enabled by analytical insights, social collaboration, and real-time access to information on any device, so you can better manage sales performance, motivate sales people and mentor best practices, while ensuring that incentive compensation plans supports your strategy.
When the right approach is applied, analytics can drive more effective marketing strategies. While marketers understand the role analytics plays within the organization, most are not leveraging analytics to really drive enterprise performance. We surveyed 100+ business leaders to understand the state of analytics maturity across today’s leading organizations, uncovering common challenges teams are facing in their quest to use data and analytics to deliver a competitive advantage.
What We Uncovered:
- 73% of analytic professionals claim to work for an analytically-driven company
- Only 42% of companies have a strategy for using analytics across the enterprise
- Just 38% of companies share results of their analytic insights outside their department
- 81% of organizations rely on 3rd parties for at least some portion of their analysis
Download the report to learn how marketers, like yourself, view themselves in light of using analytics to drive their business.
"What would you do if you didn’t have to rely on disparate analytics solutions to meet the needs of business users while following the rules of IT?
View this 'Charting Your Analytical Future' webinar to learn about a world of innovation and independence for users that does not limit the confidence and controls of IT.
With the cognitive-guided self-service features available in IBM business analytics solutions, more users than ever before can get the answers they need. Next-generation business analytics capabilities make it possible to access relevant data, prepare it for analysis and understand performance. But it doesn’t stop there. Users can package the results in a visually-appealing format and share them throughout the organization.
Don’t miss this opportunity to hear how you can:
* Benefit from advanced analytics without the complexity
* Operationalize insights and dashboards from a collection of trusted data sources
* Tell your story with rich visualizations and geospati
As the information age matures, data has become the most
powerful resource enterprises have at their disposal. Businesses
have embraced digital transformation, often staking their
reputations on insights extracted from collected data. While
decision-makers hone in on hot topics like AI and the potential of
data to drive businesses into the future, many underestimate the
pitfalls of poor data governance. If business decision-makers can’t
trust the data within their organization, how can stakeholders and
customers know they are in good hands? Information that is not
correctly distributed, or abandoned within an IT silo, can prove
harmful to the integrity of business decisions.
In search of instant analytical insights, businesses often prioritize data
access and analysis over governance and quality. However, without
ensuring the data is trustworthy, complete and consistent, leaders
cannot be confident their decisions are rooted in facts and reality
Retailers continue to collect this data and many have made good use of it, segmenting and targeting customers and rewarding loyal behavior with discounts and offers. Still, many sense that there’s untapped potential. They’re right. With the cost of data storage plummeting and the capabilities of analytical tools on the rise, this data’s value is set to skyrocket. John Bible, Senior Director of Retail Data Science and Insight at Oracle Retail shares his view on how insights from these vast data storehouses can scientifically inform retailers’ decision-making in critical strategic, tactical and operational areas, including category management, shelf space allocation and new product introductions.
The insurance industry stands on the precipice of change, with waves of innovation and disruption driving new possibilities across all departments, including pricing, underwriting, claims, and fraud.
This webinar recording of a live panel debate is ideal for insurance professionals wanting to understand how best to unlock the possibilities created by advanced analytical techniques such as Artificial Intelligence (AI), Machine Learning (ML), and others.
This TIBCO and Marketforce webinar on “The Fourth Industrial Revolution in Insurance” includes speakers Ian Thompson, chief claims officer at Zurich; David Williams, chief underwriting officer at AXA; and Clare Lunn, GI fraud director at LV=. The panel discusses:
Moving towards the algorithmic insurer: the opportunities created by AI and ML
How insurers can become more agile in the face of new innovations and disruptive technologies
How the industry can turn structured and unstructured data into insights
How we fuel our vehicles, heat our homes, and power our industries is undergoing fundamental change. Well-deployed but inefficient technologies, such as internal combustion engine cars and oil/gas boilers are being replaced with electrified and higher-efficiency alternatives. And renewables such as sunlight, wind, thermal, and others, supported by next generation battery storage, are fueling an evergreater share of energy demand.
Published By: Tableau
Published Date: Apr 13, 2018
In this whitepaper, discover the benefits of expanding your analytics toolkit. Combine Excel’s data collection and management capabilities with Tableau’s intuitive, analytical power to transform your raw data into actionable insights. Focus on the questions that take your data beyond the spreadsheet.
Read more at about this partnership.
Forrester names Adobe as a Leader in customer analytics, according to the Forrester Wave: Customer Analytics Solutions, Q2 2018 report.
• We’re a Leader. But we won’t stop there. Adobe Analytics provides a superior product, executive vision, and strategy. We understand the needs of today’s marketers and customer insights professions, while staying ahead
of the curve on future analytics trends.
• Adobe Analytics fuels insight-driven customer experiences. Adobe has turned its mantra of “Make Experience Your Business” inward, by developing a marketer-friendly solution that doesn’t skimp on advanced analytical functionality.
• Adobe Analytics excels at real-time conversion of insights into action, superior usability, and AI-powered customer journey analytics.
• Adobe Analytics’ capabilities, such as Virtual Analyst, powered by Adobe Sensei, use artificial intelligence and machine learning to identify anomalies, contributing factors, and segment differences. What
For data scientists and business analysts who prepare data for analytics, data management technology from SAS acts like a data filter – providing a single platform that lets them access, cleanse, transform and structure data for any analytical purpose. As it
removes the drudgery of routine data preparation, it reveals sparkling clean data and adds value along the way. And that can lead to higher productivity, better decisions and greater agility.
SAS adheres to five data management best practices that support advanced analytics
and deeper insights:
• Simplify access to traditional and emerging data.
• Strengthen the data scientist’s arsenal with advanced analytics techniques.
• Scrub data to build quality into existing processes.
• Shape data using flexible manipulation techniques.
• Share metadata across data management and analytics domains.
In today’s world, the data is flowing from all directions: social media, phones, weather, location and sensor equipped devices, and more. Competing in this digital age requires the ability to analyze all of this data, and use it to drive decisions that mitigate risk, increase customer satisfaction and grow revenue. Using a combination of proprietary software and open source technology can give your data scientists and statisticians the analytical power they need to find and act on insights quickly.
IBM® SPSS® Statistics provides all of the data analysis tools you need, and integrates with thousands of R extensions for maximum power and flexibility. In this next Data Science Central Webinar event, we will show how SPSS Statistics can help you keep up with the influx of new data and make faster, better business decisions without coding.
Think of the self-service things you use in a day. Gas pumps. ATMs. Online apps for shopping. They’re convenient and easy to use. People choose what they want, when they want – without involving others in their minute-to-minute decisions. What if your organization could treat data discovery and analytics the same way?
SAS has combined two of its visual solutions to do just that. SAS Visual Analytics and SAS Visual Statistics share the same web-based interface to provide self-service data exploration and easy-to-use interactive predictive analytics in a collaborative environment. This white paper takes a look at this convergence and outlines how these products can be used together so that everyone, even nontechnical users, can investigate data on their own, create analytical models and uncover new insights that drive competitive differentiation. Your analytics journey just got a lot easier.