How we helped our client make sense of their data and get the insights that led to success

1000's

Customer profiles cleaned

14%

Increased sales in 3 months

THE SITUATION

The digital age has fundamentally changed the way that companies learn about, interact with, and deliver to their customers. However, amassing such high volumes of data comes with its own set of challenges.

Our client (a leading telecoms service provider) was facing a very modern problem: they had too much unstructured data, which prevented them from efficiently linking information to gain valuable business understanding – including multiple customer accounts, incorrect or incomplete customer names and other missing information.

To aid the data discovery process, we delivered the following materials:

  • Assessment of data suitability to answer business “power” questions
  • Description of data sources with high-level  source mapping & relationship
  • Assessment of feasibility of data  integration
Data acquisition, cleaning and enrichment 1
Data acquisition, cleaning and enrichment 2

THE SOLUTION

To deliver meaningful insights on the client’s customer base, we needed to perform exploratory analysis of the available data and then clean and enrich the in-house data.

The first step was to assess the data sources so that we could learn more about how the information was initially recorded and linked with other sets. Then, working with the client, we took a closer look at the existing company data to identify all of the relevant sources, before proceeding.

After understanding and linking the relevant data ecosystem, we built a simple but impactful flow (fuzzy matching) which looked for similar customer names and keywords to identify the actual accounts of existing clients. This helped to reduce the manual effort from an estimated 30 man-days to just under 5 man-days.

By working on a clean dataset, we also set out to enrich what our client knew about their existing customers by linking the internal data to an external database, web scraping and manually filling in the gaps where no other means could help. The process resulted in an over 10 000 potential clients database, based on the existing customer profiles.

Data acquisition, cleaning and enrichment 3

THE SUCCESS

We can classify our success in three different areas:

 

Data Discovery: Taking 100 disjointed and unclear datasets, we identified the dependencies together with useful and missing variables to clearly see the gaps and misalignments in data, and identify relevant data sources.

Data Cleansing: We eliminated repeated data for several thousand customer profiles and analysed all accounts in the data warehouse to create systematic profiles for all customers. This allowed sales reps to have a single view of the customer base and overall journey.

Data Enriching: We provided a database with 12,000 prospects for our client, with profiles similar to the existing ones to match the datasets. We enriched all existing customer profiles with descriptive statistics, relevant contact information and user reviews. The enriched datasets helped the client to obtain new customers and increased sales by 14% within the first 3 months of using the new datasets.

How we helped our client make sense of their data and get the insights that led to success

1000's

Customer profiles cleaned

14%

Increased sales in 3 months

THE SITUATION

The digital age has fundamentally changed the way that companies learn about, interact with, and deliver to their customers. However, amassing such high volumes of data comes with its own set of challenges.

Our client (a leading telecoms service provider) was facing a very modern problem: they had too much unstructured data, which prevented them from efficiently linking information to gain valuable business understanding – including multiple customer accounts, incorrect or incomplete customer names and other missing information.

To aid the data discovery process, we delivered the following materials:

  • Assessment of data suitability to answer business “power” questions
  • Description of data sources with high-level source mapping & relationship
  • Assessment of feasibility of data integration
Data acquisition, cleaning and enrichment 1
Data acquisition, cleaning and enrichment 5

THE SOLUTION

To deliver meaningful insights on the client’s customer base, we needed to perform exploratory analysis of the available data and then clean and enrich the in-house data.

The first step was to assess the data sources so that we could learn more about how the information was initially recorded and linked with other sets. Then, working with the client, we took a closer look at the existing company data to identify all of the relevant sources, before proceeding.

After understanding and linking the relevant data ecosystem, we built a simple but impactful flow (fuzzy matching) which looked for similar customer names and keywords to identify the actual accounts of existing clients. This helped to reduce the manual effort from an estimated 30 man-days to just under 5 man-days.

By working on a clean dataset, we also set out to enrich what our client knew about their existing customers by linking the internal data to an external database, web scraping and manually filling in the gaps where no other means could help. The process resulted in an over 10 000 potential clients database, based on the existing customer profiles.

Data acquisition, cleaning and enrichment 3

THE SUCCESS

We can classify our success in three different areas:

 

Data Discovery: Taking 100 disjointed and unclear datasets, we identified the dependencies together with useful and missing variables to clearly see the gaps and misalignments in data, and identify relevant data sources.

Data Cleansing: We eliminated repeated data for several thousand customer profiles and analysed all accounts in the data warehouse to create systematic profiles for all customers. This allowed sales reps to have a single view of the customer base and overall journey.

Data Enriching: We provided a database with 12,000 prospects for our client, with profiles similar to the existing ones to match the datasets. We enriched all existing customer profiles with descriptive statistics, relevant contact information and user reviews. The enriched datasets helped the client to obtain new customers and increased sales by 14% within the first 3 months of using the new datasets.

How we helped our client make sense of their data and get the insights that led to success

1000's

Customer profiles cleaned

14%

Increased sales in 3 months

THE SITUATION

The digital age has fundamentally changed the way that companies learn about, interact with, and deliver to their customers. However, amassing such high volumes of data comes with its own set of challenges.

Our client (a leading telecoms service provider) was facing a very modern problem: they had too much unstructured data, which prevented them from efficiently linking information to gain valuable business understanding – including multiple customer accounts, incorrect or incomplete customer names and other missing information.

To aid the data discovery process, we delivered the following materials:

  • Assessment of data suitability to answer business “power” questions
  • Description of data sources with high-level source mapping & relationship
  • Assessment of feasibility of data integration
Data acquisition, cleaning and enrichment 1
Data acquisition, cleaning and enrichment 2

THE SOLUTION

To deliver meaningful insights on the client’s customer base, we needed to perform exploratory analysis of the available data and then clean and enrich the in-house data.

The first step was to assess the data sources so that we could learn more about how the information was initially recorded and linked with other sets. Then, working with the client, we took a closer look at the existing company data to identify all of the relevant sources, before proceeding.

After understanding and linking the relevant data ecosystem, we built a simple but impactful flow (fuzzy matching) which looked for similar customer names and keywords to identify the actual accounts of existing clients. This helped to reduce the manual effort from an estimated 30 man-days to just under 5 man-days.

By working on a clean dataset, we also set out to enrich what our client knew about their existing customers by linking the internal data to an external database, web scraping and manually filling in the gaps where no other means could help. The process resulted in an over 10 000 potential clients database, based on the existing customer profiles.

Data acquisition, cleaning and enrichment 3

THE SUCCESS

We can classify our success in three different areas:

 

Data Discovery: Taking 100 disjointed and unclear datasets, we identified the dependencies together with useful and missing variables to clearly see the gaps and misalignments in data, and identify relevant data sources.

Data Cleansing: We eliminated repeated data for several thousand customer profiles and analysed all accounts in the data warehouse to create systematic profiles for all customers. This allowed sales reps to have a single view of the customer base and overall journey.

Data Enriching: We provided a database with 12,000 prospects for our client, with profiles similar to the existing ones to match the datasets. We enriched all existing customer profiles with descriptive statistics, relevant contact information and user reviews. The enriched datasets helped the client to obtain new customers and increased sales by 14% within the first 3 months of using the new datasets.