Through the lens of data analysis, brands can begin to predict who will churn, why and when. But traditional analytics cannot paint a complete picture of consumer behavior because it's not able to leverage the full array and volume of data that has now become available. With Big Data 2.0 Analytics, brands can now tap into a wider variety of data, process inputs with remarkable speed and accuracy, and deliver real-time personalized recommendations for each customer at the most granular level. to learn about how the Actian Analytics platform can create transformative value for your organization, please visit us at www.actian.com

1. Customer Loyalty Hinges on Trust

2. consumers have become more vocal about their choices and
preferences than ever before

3. Online, on mobile devices, and in the social sphere, they
broadcast their likes and dislikes with great clarity

4. But the brands that serve them often fail to hear them until it’s
too late

5. Historic analysis of consumer behavior is a poor predictor of
what the consumer will do today

6. In this very moment, millions of consumers contemplate their allegiances and
consider making the switch to a rival brand

7. the cost of acquiring a new customer far outweighs the cost of
keeping one

8. to safeguard customer loyalty and stem churn, organizations must learn to
monitor the vital signs of consumer sentiment in real time

9. To evolve from explanation to prediction and beyond - toward analytic insights that
prompt personal, timely actions that drive customer value and delight.

10. It’s no secret that data holds the key yet what most organizations think of as
data sources is only the tip of the iceberg

11. The last several years have seen an explosive growth not only in
the size of data but also in the sheer variety of available data

12. The heartbeat of consumer sentiment resonates across call center records,
machine log files, social media posts, email, and web clickstream data

13. Through the lens of data analysis, brands can begin to predict
who will churn, why and when

14. Traditional analytics cannot paint a complete picture of consumer behavior
because it’s not able to leverage the full array and volume of data that has
now become available

15. With Big Data 2.0 Analytics, brands can now tap into a wider
variety of data,

16. process inputs with remarkable speed and accuracy,

17. and deliver real-time personalized recommendations for each
customer at the most granular level.

18. Profound insight into customer behavior becomes possible when
diverse forms of data can be combined in novel ways,

19. revealing patterns and correlations in the torrential deluge of
data.

20. With Big Data 2.0 Analytics, brands can create targeted offers and proactively
solve customer issues

21. Where guesswork and instinct once drove business decisions,
brands can now begin to implement a data-driven strategy

22. With Big Data 2.0 Analytics, every data source is now at their
fingertips.

23. And the ability to derive insights from data is no longer the privilege of select
few but available on-demand across the entire organization

24. By identifying the needs of potential consumers and improving customer
experience through personalization,

25. brands will not only ensure customer loyalty

26. but are likely to see a significant improvement to their bottom
line

27. Thank you!