C1 - Internal use 

 Learning Launch – Collecting and optimizing product information for online channels 

 Challenge & Selection 

 I am a member of my organization ’s Marketing Department and our challenge is to improve the online   friendliness of the product information present on the e - commerce pages of our products to drive further   sales on this increasingly growing channel . Today , different teams are involved in the production and   management of the product information – the comprehensiveness and quality is quite inconsistent   between product categories and often just copied from the product pack meant for offline distribution . 

 We have already analysed and assessed a few options to optimize the attractiveness of our products pages   online and ways to drive further consumer interest and conversion . Our main assumption is that currently ,   most teams are not focusing on the online channel , so the production and availability of information for   this channel is often deprioritised . As our organization sells a very large number of products online , we   have decided to test internally a unique tool to centralize , manage and optimise our product information   for the online channel : product name , description , how to use , size and weight of the product , etc . Two   main teams are part of this project - the Product Development team and Marketing Department , with   around 30 people involved . The objective is to test and learn from an initial trial of this product   information management tool , using ten of the most popular products we sell online , and to identify   which ways of working within our organisation could efficiently support the tool adoption . 

 Application 

 For this learning launch , we selected 3 to 4 bestselling products for each of our top selling categories   online . We wanted to identify for these 10 products , which kind of product information was already   available , which teams where providing it , if the Marketing teams would be able to pool it and optimize it   for our online product pages using the product information management tool prototype . 

 For that , we had first to go through a workshop to map which teams where actually owning the different   types of product information and who to contact to collect it . This was particularly useful to identify and   clarify which information we needed ( must have and nice to have for online usage ) and who were the   stakeholders across the organisation to interact with . 

 Then , we also designed a template to upload in the product information in our tool prototype to ensure   the targeted information to be collected from these sources was consistent – as different teams were   providing it depending on the category and type of product . This helped get a first round of the   information available , and the kind of processes and stakeholders to be involved for consistent collection . 

 Finally yet importantly , we focused on pooling the usage and user - friendliness of the tool prototype . We   trained the end - users from the Product Development and the Marketing teams on how to use the tool –   from uploading the information collected with other teams , to editing it to make it e - commerce friendly   and sharing it for usage . Then , we shadowed the teams on their actual usage , to understand how the tool   was being used to process and optimise the information . After 2 weeks of usage , we collected users ’   feedback through a survey on the tool prototype and learning launch experience overall . 

 We also conducted one retrospective meeting to go through the feedback comments and wrap up on the   learnings of the launch , from a tool and ways of working perspective . 

 C1 - Internal use 

 Insight 

 By applying the learning launch tool , we were able to assess concretely our assumption regarding product   information management for the online channel . 

 We were able to interact with many teams involved in the product information production . This helped   confirm that product information is very scattered across the teams , and does require a lot of initial effort   to be pooled in a consistent way and format in a single place . However , it also made us reconsider the   scope of the teams that should be involved in the collection and the input of the product information in   the tool . Initially , we were thinking to streamline the process of the collection by solely giving this   responsibility to the Product Development and Marketing Teams . This implies a lot of additional time- consuming coordination , especially on the logistics information ( product package dimension & weight ) ,   and even data processing to upload the template on the tool . The value added of the Marketing team is   to optimise the information to make it relevant for the online channel , showing that a better balance   needs to be defined in the ways of working supporting the tool – more teams could be involved and take   responsibility to provide and share the product information directly in the tool . 

 In addition , though it was relevant to include different product categories in the learning launch , including   less popular products in the test would have helped assess the quantity and quality of the product   information available . For these products , the information collection could potentially be even more   exhaustive to ensure good data quality for our online product pages . 

 Given these learnings , the team will review the processes and adjust the tool to ensure all teams can   provide the relevant value in terms of product information optimized for online channels . 

 Approach 

 The learning tool was a great tool to use at this stage , as we were clear on some of the assumptions but   not all . It was definitely a great way as well to involve for the broader organization , involving different   teams through the very intensive coordination work to collect the information and information   processing . We shall use the learnings collected from all teams and adjust the tool design , as well as , most   importantly the teams involved to provide a balanced solution that helps us craft the best product   information for online sales . We will definitely test the next version of the prototype to fine tune further   the tool and supporting processes before full roll out across all products ! 


EMAIL: 
ID_NUM: 
NAME_STUDENT: 
PHONE_NUM: 
STREET_ADDRESS: 
URL_PERSONAL: 
USERNAME: 

### Task: You are a PII (Personal Identity Information) Detection. Given a essays written by students, you have to identify ONLY the following:
NAME_STUDENT - The full or partial name of a student that is not necessarily the author of the essay. This excludes instructors, authors, and other person names.
EMAIL - A student’s email address.
USERNAME - A student's username on any platform.
ID_NUM - A number or sequence of characters that could be used to identify a student, such as a student ID or a social security number.
PHONE_NUM - A phone number associated with a student.
URL_PERSONAL - A URL that might be used to identify a student.
STREET_ADDRESS - A full or partial street address that is associated with the student, such as their home address.
### Input: C1 - Internal use 

 Learning Launch – Collecting and optimizing product information for online channels 

 Challenge & Selection 

 I am a member of my organization ’s Marketing Department and our challenge is to improve the online   friendliness of the product information present on the e - commerce pages of our products to drive further   sales on this increasingly growing channel . Today , different teams are involved in the production and   management of the product information – the comprehensiveness and quality is quite inconsistent   between product categories and often just copied from the product pack meant for offline distribution . 

 We have already analysed and assessed a few options to optimize the attractiveness of our products pages   online and ways to drive further consumer interest and conversion . Our main assumption is that currently ,   most teams are not focusing on the online channel , so the production and availability of information for   this channel is often deprioritised . As our organization sells a very large number of products online , we   have decided to test internally a unique tool to centralize , manage and optimise our product information   for the online channel : product name , description , how to use , size and weight of the product , etc . Two   main teams are part of this project - the Product Development team and Marketing Department , with   around 30 people involved . The objective is to test and learn from an initial trial of this product   information management tool , using ten of the most popular products we sell online , and to identify   which ways of working within our organisation could efficiently support the tool adoption . 

 Application 

 For this learning launch , we selected 3 to 4 bestselling products for each of our top selling categories   online . We wanted to identify for these 10 products , which kind of product information was already   available , which teams where providing it , if the Marketing teams would be able to pool it and optimize it   for our online product pages using the product information management tool prototype . 

 For that , we had first to go through a workshop to map which teams where actually owning the different   types of product information and who to contact to collect it . This was particularly useful to identify and   clarify which information we needed ( must have and nice to have for online usage ) and who were the   stakeholders across the organisation to interact with . 

 Then , we also designed a template to upload in the product information in our tool prototype to ensure   the targeted information to be collected from these sources was consistent – as different teams were   providing it depending on the category and type of product . This helped get a first round of the   information available , and the kind of processes and stakeholders to be involved for consistent collection . 

 Finally yet importantly , we focused on pooling the usage and user - friendliness of the tool prototype . We   trained the end - users from the Product Development and the Marketing teams on how to use the tool –   from uploading the information collected with other teams , to editing it to make it e - commerce friendly   and sharing it for usage . Then , we shadowed the teams on their actual usage , to understand how the tool   was being used to process and optimise the information . After 2 weeks of usage , we collected users ’   feedback through a survey on the tool prototype and learning launch experience overall . 

 We also conducted one retrospective meeting to go through the feedback comments and wrap up on the   learnings of the launch , from a tool and ways of working perspective . 

 C1 - Internal use 

 Insight 

 By applying the learning launch tool , we were able to assess concretely our assumption regarding product   information management for the online channel . 

 We were able to interact with many teams involved in the product information production . This helped   confirm that product information is very scattered across the teams , and does require a lot of initial effort   to be pooled in a consistent way and format in a single place . However , it also made us reconsider the   scope of the teams that should be involved in the collection and the input of the product information in   the tool . Initially , we were thinking to streamline the process of the collection by solely giving this   responsibility to the Product Development and Marketing Teams . This implies a lot of additional time- consuming coordination , especially on the logistics information ( product package dimension & weight ) ,   and even data processing to upload the template on the tool . The value added of the Marketing team is   to optimise the information to make it relevant for the online channel , showing that a better balance   needs to be defined in the ways of working supporting the tool – more teams could be involved and take   responsibility to provide and share the product information directly in the tool . 

 In addition , though it was relevant to include different product categories in the learning launch , including   less popular products in the test would have helped assess the quantity and quality of the product   information available . For these products , the information collection could potentially be even more   exhaustive to ensure good data quality for our online product pages . 

 Given these learnings , the team will review the processes and adjust the tool to ensure all teams can   provide the relevant value in terms of product information optimized for online channels . 

 Approach 

 The learning tool was a great tool to use at this stage , as we were clear on some of the assumptions but   not all . It was definitely a great way as well to involve for the broader organization , involving different   teams through the very intensive coordination work to collect the information and information   processing . We shall use the learnings collected from all teams and adjust the tool design , as well as , most   importantly the teams involved to provide a balanced solution that helps us craft the best product   information for online sales . We will definitely test the next version of the prototype to fine tune further   the tool and supporting processes before full roll out across all products !
### Output: 