• 2-Minute Preview of Astute Verbatim™ | Customer Data QA Tool

    Automatically audit 100% of CRM case data to catch and correct mistakes. Get clean, accurate customer data with no manual QA. Learn more at https://www.astutesolutions.com/products/astute-verbatim -Video Transcript- Are you bogged down manually checking your CRM data? And still only getting through a small fraction of cases? Find yourself correcting the same mistakes over and over again? You need to meet Astute Verbatim, the CRM data quality tool that checks 100% of your customer case data. With Verbatim, you get complete quality assurance, continuous improvement through deep learning, and intelligent real-time analytics. A manual QA check of your CRM may only address 1-5% of your cases. Verbatim combs through 100% of your customer cases to identify - and fix - incorrect product and rea...

    published: 03 Nov 2016
  • How to Create Customer Master Data in SAP

    How to Create Customer Master Data in SAP

    published: 25 Apr 2016
  • Blockspring for Google Sheets: Segmenting Customer Data

    Blockspring has +1000 functions that can all be used in Google Sheets. Check out the blog post here: https://api.blockspring.com/blog/blockspring-for-google-sheets In this example, we'll go through how easy it is to segment your customer list and visualize multi-dimensional data.

    published: 02 Apr 2015
  • Excel Magic Trick #184: Setup Database in Excel

    See how to create a simple database in Excel using the List or Table feature. A simple database can be created in Excel using the Excel 2003 "List" feature or the Excel 2007 "Table" feature. Fields names must be in first row (no blanks). Records are in rows (no blanks). Other data in the sheet cannot be next to the Table/List (at least one blank row or column between other data and the Table/List Keyboard shortcuts: Excel 2003 List: Ctrl + L. Excel 2007 Table: Ctrl + T. The ranges are dynamic: formulas, pivot tables, charts will all automatically update

    published: 03 Jan 2009
  • Improving Customer Experience: How to Analyse Voice of Customer Data

    Chase Petrey, Product Manager of VOC Solutions offers key insights into how a VOC platform can help you analyse your data and discover the hidden gems that will empower smarter decisions and patterns that drive a great customer experience at each point in the customer journey. For more information on Voice of Customer Solutions call 1300 725 628 or visit http://www.salmat.com.au/voc

    published: 27 Jan 2015
  • The Power of Analytics for Customer Interaction Data

    Contact Centers have become a collection of complex software processes that generate a tremendous amount of interaction data. Aria Solutions developed Visualizer, an interaction data analytics application that provides data visualization and consolidation of Genesys customer interaction events in a clearly displayed visual interface. This interface provides operational analytics insights and a “cradle-to-grave” visibility of your customers’ experiences. Learn more at http://www.ariasolutions.com/visualizer

    published: 07 Oct 2015
  • Customer Data information on the Google Maps

    upload Excel file on the google maps

    published: 27 May 2017
  • Customer Segmentation: Data Enrichment & Segmentation in Alteryx and Wave Analytics

    The Alteryx Customer Segmentation workflow showcases how an organization can optimize its marketing communications by segmenting its customer base. In this workflow, customer data from Salesforce is enriched with Dunn & Bradstreet data, blended with customer spend, and then analyzed to create and identify unique customer segments for marketing to use. The insights are then output and shared in Salesforce Wave Analytics.

    published: 24 Jun 2016
  • SAP Sharing A Customer Master Data Among Company Codes

    This is a sample of our very high quality SAP training videos we are selling at http://www.erptraining9.com. Visit this website to buy these videos for only US$499 and self-train to become an SAP consultant without leaving your home.

    published: 23 Jul 2013
  • Data Science Demo - Customer Churn Analysis

    This introduction to Data Science provides a demonstration of analyzing customer data to predict churn using the R programming language. MetaScale walks through the stops necessary to train and test multiple algorithms in order to provide the most accurate model for predicting when a customer will leave the company.

    published: 27 Sep 2015
  • Harvard i-lab | Low-Fidelity Data Mining for Customer Insights

    How can we mine survey, sales and customer data to uncover new insights into the lives and needs of our users, without a strong background in statistical analysis or code development? In this session, Almighty CSO Ian Fitzpatrick will walk through approaches to finding anomalies, commonalities and outliers in data sets — with a focus on using these to drive better qualitative research that shapes a great brand, product or service experience. Particular emphasis will be placed on combining private and public data sets to uncover hidden patterns and opportunities. The workshop itself is designed to be highly-participatory and hands-on. Participants are encouraged to bring both a laptop or tablet computer and an eagerness to collaborate with others. Learn more about the Harvard Innovation ...

    published: 04 Dec 2014
  • Customer and Vendor Master Data

    Customer Master Data Vendor Master Data

    published: 21 Sep 2015
  • What is the role of customer data in the age of engagement?

    Jakki Geiger, Senior Director of Solutions Marketing at Informatica interviews Naveen Sharma, Senior Director of Enterprise Information Management, of Cognizant, about what it means to be customer ready in the age of engagement. They discuss the fundamental role of data management and data sharing to understand your customers and engage with them in a meaningful way. Learn more: www.informatica.com/ready

    published: 14 May 2015
  • Four Ways To Optimize Customer Data for Deeper Insights Webinar March 09 2016

    To keep up with rapidly changing customer demands, businesses need to gain deeper insights into their customer data. However, business analysts must deal with increasing volumes and complexities of the data before they can deliver better insights relating to customer targeting and marketing spend. Register now for this webinar and see how business analysts can utilize 4 best practices to deal with the increasing volume and complexity of customer data: 1. BLEND your customer data from multiple sources to deliver a comprehensive view of your interactions 2. CLEANSE the data in a few simple clicks to remove bad data, outliers, and null data for better insights 3. PREDICT highest lifetime value customers without having to know how to program or code in R 4. VISUALIZE your data-driven analysi...

    published: 09 Mar 2016
  • SAP Sales & Distribution/ Master Data/ Customizing Customer Data.

    SAP Sales & Distribution Module: SAP Sales & Distribution/ Master Data/ Customizing Customer Data: Defining Account Group in SAP. Account Receivable and Account Payable. Customers Account Party (Overview). For a transaction : List of a Account Groups. - For Setting up a Customer Account. SAPRO transaction-SAP Refrence IMG- Financial Account(New)- Account receivable and Account payable.- Customer Acc - Master data. Preparation of creating master data. - Defining Account group with Screen layout. - New Entries of all new Accounts Groups - Copy one existing entry. - General Data. - Field Status. Maintain Field Status Group : Account Management Maintain Field Status Group : Sales Management - Shipping - Billing Partner Usage. ;Video by Edupedia World(www...

    published: 22 Dec 2015
  • Data & The Customer Experience | Activating Data in the New Data Economy

    Marketers use a wide variety of data to inform their marketing strategies. Some of the data contains great value but it can also be unreliable. Now brands can use each other’s data to deliver better marketing campaigns. But how can this be done safely? In the third episode of Everything You Need to Know (EYNTK) about data and customer experience, Jed Mole, European marketing director at Acxiom explains the differences between different types of data and how brands can benefit from each other’s data resources in privacy-compliant ways. Traditionally marketers have relied on first-party data to inform their marketing campaigns and marketers still see it as useful insight into customers. Research by Econsultancy last year shows that marketers felt first-party data drove the highest increase...

    published: 07 Dec 2016
2-Minute Preview of Astute Verbatim™ | Customer Data QA Tool

2-Minute Preview of Astute Verbatim™ | Customer Data QA Tool

  • Order:
  • Duration: 1:52
  • Updated: 03 Nov 2016
  • views: 9
videos
Automatically audit 100% of CRM case data to catch and correct mistakes. Get clean, accurate customer data with no manual QA. Learn more at https://www.astutesolutions.com/products/astute-verbatim -Video Transcript- Are you bogged down manually checking your CRM data? And still only getting through a small fraction of cases? Find yourself correcting the same mistakes over and over again? You need to meet Astute Verbatim, the CRM data quality tool that checks 100% of your customer case data. With Verbatim, you get complete quality assurance, continuous improvement through deep learning, and intelligent real-time analytics. A manual QA check of your CRM may only address 1-5% of your cases. Verbatim combs through 100% of your customer cases to identify - and fix - incorrect product and reason codes. Plus, it integrates with every leading CRM. Verbatim identifies errors by analyzing patterns in historical case data, and then finding discrepancies. For example, if the majority of cases with Product Code A all have similar words in their case notes, Verbatim understands that code is associated with those words. Say there's a case with similar notes but a different product code: Verbatim flags it as potentially mis-coded. In addition to training itself to recognize errors, Verbatim can also learn from your feedback. Beyond finding and fixing errors, Verbatim gives you insight into what could be causing errors in the first place. Reports break down the trends for you: Are there a few agents who need more training? A confusing reason code? Verbatim empowers you to address the cause, as well as the symptoms. Do you how many CRM errors you're missing? Schedule a live demo of Astute Verbatim today.
https://wn.com/2_Minute_Preview_Of_Astute_Verbatim™_|_Customer_Data_Qa_Tool
How to Create Customer Master Data in SAP

How to Create Customer Master Data in SAP

  • Order:
  • Duration: 2:34
  • Updated: 25 Apr 2016
  • views: 1097
videos https://wn.com/How_To_Create_Customer_Master_Data_In_Sap
Blockspring for Google Sheets: Segmenting Customer Data

Blockspring for Google Sheets: Segmenting Customer Data

  • Order:
  • Duration: 4:27
  • Updated: 02 Apr 2015
  • views: 2073
videos
Blockspring has +1000 functions that can all be used in Google Sheets. Check out the blog post here: https://api.blockspring.com/blog/blockspring-for-google-sheets In this example, we'll go through how easy it is to segment your customer list and visualize multi-dimensional data.
https://wn.com/Blockspring_For_Google_Sheets_Segmenting_Customer_Data
Excel Magic Trick #184: Setup Database in Excel

Excel Magic Trick #184: Setup Database in Excel

  • Order:
  • Duration: 7:51
  • Updated: 03 Jan 2009
  • views: 570128
videos
See how to create a simple database in Excel using the List or Table feature. A simple database can be created in Excel using the Excel 2003 "List" feature or the Excel 2007 "Table" feature. Fields names must be in first row (no blanks). Records are in rows (no blanks). Other data in the sheet cannot be next to the Table/List (at least one blank row or column between other data and the Table/List Keyboard shortcuts: Excel 2003 List: Ctrl + L. Excel 2007 Table: Ctrl + T. The ranges are dynamic: formulas, pivot tables, charts will all automatically update
https://wn.com/Excel_Magic_Trick_184_Setup_Database_In_Excel
Improving Customer Experience: How to Analyse Voice of Customer Data

Improving Customer Experience: How to Analyse Voice of Customer Data

  • Order:
  • Duration: 2:53
  • Updated: 27 Jan 2015
  • views: 367
videos
Chase Petrey, Product Manager of VOC Solutions offers key insights into how a VOC platform can help you analyse your data and discover the hidden gems that will empower smarter decisions and patterns that drive a great customer experience at each point in the customer journey. For more information on Voice of Customer Solutions call 1300 725 628 or visit http://www.salmat.com.au/voc
https://wn.com/Improving_Customer_Experience_How_To_Analyse_Voice_Of_Customer_Data
The Power of Analytics for Customer Interaction Data

The Power of Analytics for Customer Interaction Data

  • Order:
  • Duration: 2:15
  • Updated: 07 Oct 2015
  • views: 642
videos
Contact Centers have become a collection of complex software processes that generate a tremendous amount of interaction data. Aria Solutions developed Visualizer, an interaction data analytics application that provides data visualization and consolidation of Genesys customer interaction events in a clearly displayed visual interface. This interface provides operational analytics insights and a “cradle-to-grave” visibility of your customers’ experiences. Learn more at http://www.ariasolutions.com/visualizer
https://wn.com/The_Power_Of_Analytics_For_Customer_Interaction_Data
Customer Data information on the Google Maps

Customer Data information on the Google Maps

  • Order:
  • Duration: 3:07
  • Updated: 27 May 2017
  • views: 14
videos
upload Excel file on the google maps
https://wn.com/Customer_Data_Information_On_The_Google_Maps
Customer Segmentation: Data Enrichment & Segmentation in Alteryx and Wave Analytics

Customer Segmentation: Data Enrichment & Segmentation in Alteryx and Wave Analytics

  • Order:
  • Duration: 7:39
  • Updated: 24 Jun 2016
  • views: 576
videos
The Alteryx Customer Segmentation workflow showcases how an organization can optimize its marketing communications by segmenting its customer base. In this workflow, customer data from Salesforce is enriched with Dunn & Bradstreet data, blended with customer spend, and then analyzed to create and identify unique customer segments for marketing to use. The insights are then output and shared in Salesforce Wave Analytics.
https://wn.com/Customer_Segmentation_Data_Enrichment_Segmentation_In_Alteryx_And_Wave_Analytics
SAP Sharing A Customer Master Data Among Company Codes

SAP Sharing A Customer Master Data Among Company Codes

  • Order:
  • Duration: 1:12
  • Updated: 23 Jul 2013
  • views: 38
videos
This is a sample of our very high quality SAP training videos we are selling at http://www.erptraining9.com. Visit this website to buy these videos for only US$499 and self-train to become an SAP consultant without leaving your home.
https://wn.com/Sap_Sharing_A_Customer_Master_Data_Among_Company_Codes
Data Science Demo - Customer Churn Analysis

Data Science Demo - Customer Churn Analysis

  • Order:
  • Duration: 9:30
  • Updated: 27 Sep 2015
  • views: 4290
videos
This introduction to Data Science provides a demonstration of analyzing customer data to predict churn using the R programming language. MetaScale walks through the stops necessary to train and test multiple algorithms in order to provide the most accurate model for predicting when a customer will leave the company.
https://wn.com/Data_Science_Demo_Customer_Churn_Analysis
Harvard i-lab | Low-Fidelity Data Mining for Customer Insights

Harvard i-lab | Low-Fidelity Data Mining for Customer Insights

  • Order:
  • Duration: 1:08:14
  • Updated: 04 Dec 2014
  • views: 1176
videos
How can we mine survey, sales and customer data to uncover new insights into the lives and needs of our users, without a strong background in statistical analysis or code development? In this session, Almighty CSO Ian Fitzpatrick will walk through approaches to finding anomalies, commonalities and outliers in data sets — with a focus on using these to drive better qualitative research that shapes a great brand, product or service experience. Particular emphasis will be placed on combining private and public data sets to uncover hidden patterns and opportunities. The workshop itself is designed to be highly-participatory and hands-on. Participants are encouraged to bring both a laptop or tablet computer and an eagerness to collaborate with others. Learn more about the Harvard Innovation Lab at http://i-lab.harvard.edu/ and follow us on Twitter at http://twitter.com/innovationlab and like us on Facebook athttps://www.facebook.com/harvardinnovationlab
https://wn.com/Harvard_I_Lab_|_Low_Fidelity_Data_Mining_For_Customer_Insights
Customer and Vendor Master Data

Customer and Vendor Master Data

  • Order:
  • Duration: 47:12
  • Updated: 21 Sep 2015
  • views: 1221
videos
Customer Master Data Vendor Master Data
https://wn.com/Customer_And_Vendor_Master_Data
What is the role of customer data in the age of engagement?

What is the role of customer data in the age of engagement?

  • Order:
  • Duration: 1:26
  • Updated: 14 May 2015
  • views: 361
videos
Jakki Geiger, Senior Director of Solutions Marketing at Informatica interviews Naveen Sharma, Senior Director of Enterprise Information Management, of Cognizant, about what it means to be customer ready in the age of engagement. They discuss the fundamental role of data management and data sharing to understand your customers and engage with them in a meaningful way. Learn more: www.informatica.com/ready
https://wn.com/What_Is_The_Role_Of_Customer_Data_In_The_Age_Of_Engagement
Four Ways To Optimize Customer Data for Deeper Insights Webinar March 09 2016

Four Ways To Optimize Customer Data for Deeper Insights Webinar March 09 2016

  • Order:
  • Duration: 57:52
  • Updated: 09 Mar 2016
  • views: 351
videos
To keep up with rapidly changing customer demands, businesses need to gain deeper insights into their customer data. However, business analysts must deal with increasing volumes and complexities of the data before they can deliver better insights relating to customer targeting and marketing spend. Register now for this webinar and see how business analysts can utilize 4 best practices to deal with the increasing volume and complexity of customer data: 1. BLEND your customer data from multiple sources to deliver a comprehensive view of your interactions 2. CLEANSE the data in a few simple clicks to remove bad data, outliers, and null data for better insights 3. PREDICT highest lifetime value customers without having to know how to program or code in R 4. VISUALIZE your data-driven analysis and increase your speed to insight Attend this webinar and see how Alteryx and Microsoft Power BI enable business analysts to optimize customer data in order to generate deeper insights.
https://wn.com/Four_Ways_To_Optimize_Customer_Data_For_Deeper_Insights_Webinar_March_09_2016
SAP Sales & Distribution/ Master Data/ Customizing Customer Data.

SAP Sales & Distribution/ Master Data/ Customizing Customer Data.

  • Order:
  • Duration: 30:00
  • Updated: 22 Dec 2015
  • views: 670
videos
SAP Sales & Distribution Module: SAP Sales & Distribution/ Master Data/ Customizing Customer Data: Defining Account Group in SAP. Account Receivable and Account Payable. Customers Account Party (Overview). For a transaction : List of a Account Groups. - For Setting up a Customer Account. SAPRO transaction-SAP Refrence IMG- Financial Account(New)- Account receivable and Account payable.- Customer Acc - Master data. Preparation of creating master data. - Defining Account group with Screen layout. - New Entries of all new Accounts Groups - Copy one existing entry. - General Data. - Field Status. Maintain Field Status Group : Account Management Maintain Field Status Group : Sales Management - Shipping - Billing Partner Usage. ;Video by Edupedia World(www.edupediaorld.com), Online Education. Click here (https://www.youtube.com/playlist?list=PLJumA3phskPHjbd-dsViJ1Kg8L7AKZdDT) for more videos.All Rights Reserved.
https://wn.com/Sap_Sales_Distribution_Master_Data_Customizing_Customer_Data.
Data & The Customer Experience | Activating Data in the New Data Economy

Data & The Customer Experience | Activating Data in the New Data Economy

  • Order:
  • Duration: 4:55
  • Updated: 07 Dec 2016
  • views: 1634
videos
Marketers use a wide variety of data to inform their marketing strategies. Some of the data contains great value but it can also be unreliable. Now brands can use each other’s data to deliver better marketing campaigns. But how can this be done safely? In the third episode of Everything You Need to Know (EYNTK) about data and customer experience, Jed Mole, European marketing director at Acxiom explains the differences between different types of data and how brands can benefit from each other’s data resources in privacy-compliant ways. Traditionally marketers have relied on first-party data to inform their marketing campaigns and marketers still see it as useful insight into customers. Research by Econsultancy last year shows that marketers felt first-party data drove the highest increase in customer value. But first-party data while valuable, has its limitations. In the video, Mole argues that all data is not equal and there is a better way for brands to monetize on their data in secure ways. He introduces ‘safe haven’ technology where brands can put their de-identified data through a trusted third-party’s ‘black box’ for a mutually beneficial data-sharing relationship. “It’s the trusted third-party that allows each brand to benefit from the combined insights of their data without ever having access or seeing each other’s data,” says Mole. Catch up on last week’s episode which examined the customer recognition gap. Next week’s episode will tackle the new customer view. Subscribe & Follow The Drum YouTube: https://www.youtube.com/user/TheDrumReel Website: http://www.thedrum.com/ Facebook: https://www.facebook.com/thedrumpage Twitter: https://twitter.com/thedrum Instagram: https://instagram.com/thedrummag Pinterest: https://uk.pinterest.com/thedrum/
https://wn.com/Data_The_Customer_Experience_|_Activating_Data_In_The_New_Data_Economy
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