Text Matching and Analytics

A Typical Business Problem

It is very common for businesses to have many versions of the same data. For example, a business may have customer records in systems for contact management, licensing, sales and finance. The situation is often made worse when a business wants to access external data for its customer from a third party.

It is rare to find that all the systems have the same name for each customer. This happens naturally as it is common to abbreviate many parts of a company’s name. These differences in description can also prevent sales processes from operating correctly and will impact revenue generation.

JTA Solutions

We help our clients to improve their business performance by leveraging superior data and insights across their organization, growing their knowledge and developing impactful go-to-market strategies, audience targeting and nurturing of prospects.

We can deploy a variety of fuzzy matching and direct matching techniques to solve these issues. On a recent sales matching project, we were able to increase the match rate from 18% to 92%.

Read our whitepaper on text matching

The Secret Recipe to Success

Text matching can be fraught with problems. Here are some techniques recommended by JTA to make your text matching exercise a success:

Good text matching starts with data cleaning. Matches might fail because of differences in case, extra white space or use of accents with Latin languages. Data cleaning can help to minimise these problems.
Understand how languages work. A matching algorithm may need to apply different techniques when matching different languages. Chinese is very different to Italian.
Keep a database of common abbreviations and apply them consistently to the input data. If you have records for “ACME Incorporated” and “ACME inc.” then change them to both have a preferred consistent format. Doing this will allow you to get a lot more direct matches without resorting to fuzzy matching algorithms.

- Maximize the number of direct matches that you make in order to minimize the number of fuzzy matches required.
- Never accept the results from matching in a business process without a validation process to test that the match is correct. Only accept matches which pass the test with a defined level of confidence.
- Be careful when using fuzzy matching to build algorithms that are efficient as they can require a lot of computing resources. Run times must be realistic in the context of the business process as a whole.
- Use machine learning techniques so that your matching engine will train itself over time and remember matches. You want the business process to get ever more accurate and faster and also reduce the amount of manual time needed.

Our Other Data Solutions Services

Business Intelligence (BI)

From simple reports to complete BI strategy that fully meets your business needs, we can help. Enjoy the flexibility that mobile and self-service BI brings to an organization without re-inventing the wheel.

Market Segmentation

Market segmentation involves dividing customers into groups of people with similar characteristics or interests in order to make your marketing more effective.

Data Modeling

We have built many market models for our clients over the years allowing them to better understand the dynamics of the market and also to measure their performance. Market models explain what happened in the recent past and also allow us to forecast what is likely to happen.

Advanced Analytics

We can apply complex algorithms and Machine Learning and techniques of predictive analytics to a great variety of problems. Advanced analytics is a subset of data science that uses high-level techniques to predict future trends and behaviours.

Data Processing

Good Data Science starts with a deep understanding of how data should be manipulated and stored. Traditional data and big data need different approaches but the underlying discipline is the same. The way we store data differs greatly and we can advise on how to adapt your platforms for better insight generation.

Integrated Security

We take integrated security very seriously at JTA. We have the most stringent security practices and hold ourselves to a higher standard than most. JTA can build dashboards that intelligently adapt their content depending on who is viewing it to help users comply with corporate accountability legislation.

Predictive Maintenance

Predictive maintenance is a benefit that we can bring to an organization by predicting failures and quality issues. This can avoid downtime and reduce maintenance costs.

Customer Churn

Using data prediction to identify when a certain customer is at high risk of churn allow clients to prevent attrition and keep existing clients. This helps immeasurably and keeps you with one in the hand rather than two in the bush.

Internet of Things

The Internet of Things is the network of small devices that have an embedded processor to measure, control and connect to the internet. Many such devices benefit from sophisticated algorithms and data science techniques. We can develop solutions ready to roll out for deployment on the microcontroller.

Outsourced Analysis

Companies which prefer to outsource data analytics instead of deploying a solution in-house can use JTA to form a virtual team to manage outsourced data analysis. Our team would typically access your data and your infrastructure and do the analysis remotely.

Market Basket Analysis

Market Basket Analysis help companies understand how their customers make purchases. The objective is to help to configure sales promotions, loyalty programs and store layout.

Text Matching and Analytics