What would you do with an extra 15 minutes in your day? How about a few extra hours?
Give yourself the time to achieve more – fly through your data matching like a superhero with these quick tips:
- Use Match2Lists! Take a free trial (or login) to match data, merge lists and resolve duplicates lightning fast in the cloud.
- Be prepared. Save valuable time by having the lists you want to use ready. Upload them all to Match2Lists in text file format now, and you won’t need to hunt for them one-by-one later on.
- Give your Project a descriptive name that you’ll easily remember. ‘2011 Q1 Customers vs. 2010 Q1 Customers’ is more helpful than merely ‘Customers’. When you’ve got several active Projects, you’ll be glad you named them wisely and know which is what!
- It usually makes sense to designate the shorter of your 2 lists as your Source List, because it’s quicker to match a long list against a short list than vice versa.
- Use the Match Visualiser Auto Approve facility to batch validate results that don’t require individual scrutiny, or Auto Reject results with less than your selected minimum match score.
- Collaborate with colleagues and third parties to accelerate your project over the finish line. Upgrade to an Enterprise Account to share your Match2Lists data and projects online.
We hope you find these quick tips helpful. Until next time, happy matching!
P.S. Have we missed out your favourite trick for super-fast data matching, merging and deduping with Match2Lists? Leave a comment to add your top tips to the list.
We have been asked a few times now for a more detailed explanation of how the Match weightings work and how they affect the Match score.
The purpose of the Match weighting is to allow you to determine the importance that you want to place on each data description.
The match score is calculated by adding together the score of all the data descriptions and dividing by the number of descriptions. The weighting determines what percentage of the score for each data description is applied to the match score.
The example below will show how the match weighting affects the match score:
- Company Name – Weighting 100%
- Address – Weighting 100%
- City – Weighting 50%
- Postcode – Weighting 100%
Each description adds to the match score as below:
- Company Name contribution to MatchScore = (100% / 350% = approx 29%)
- Address contribution to MatchScore = (100% / 350% = approx 29%)
- City contribution to MatchScore = (50% / 350% = approx 14%)
- Postcode contribution to MatchScore = (100% / 350% = approx 29%)
Therefore by adjusting the match weighting you can determine the importance and contribution that each data description adds to the match score and can therefore adjust these weightings to help find new matches emphasising different elements of your data.
We have been asked on several occasions why you need to specify which country a list pertains to and why can’t we just have an international setting.
The simple answer is accuracy, but let’s not leave it at that. I’d like to share with you some of the nuances that we see on a regular basis, to help you understand a little of the work that has gone on behind the scenes to ensure you get the best matching results possible.
In the coming months I will look to discuss country specific nuances in deeper detail and share the learnings and experiences that we have had matching data for large multi-national organisations across the globe. I’ll also show some of the approaches we have taken to tackle these issues at Match2Lists.
Needless to say, it’s not a case of one logic rule works for all. Different elements of an address need to be processed and interpreted in different ways, and country nuances can and do have significant impact on these rules. Specifying which country your list is related to helps Match2Lists use the most appropriate rules and logic to achieve the best matching results for you.
Several people have asked on occasion if it was possible to increase the width of the Match Results, so one of the amendments we have made to the visualizer is the addition of sizing options for validating your match results.
Using these buttons you can increase the size of the windows displaying the match results making it easier to read longer company names and addresses. A useful feature when looking for the best possible match.
You can also switch back to the smaller option to view more of the potential matches side by side without scrolling – this is particularly helpful when you’re de-duping a list or looking for multiple matches.
Today we launched an updated version of our acclaimed Match Visualizer which includes new functionality to continue our quest to speed up the process of manual verification of Match Results.
The new changes include a filter option alongside the Match Weightings that enable you to filter out less likely match results and chunk up the approvals to an even greater degree than ever before.
The Automatic approval process works in conjunction with these new filters, which enables you to verify and automatically approve even more matches and once again radically cut down the time required for complex data matching like never before.
We will be adding a new video soon to show how you can make the most effective use of this new feature.
In short, if you have multiple company names you should be using them during the data matching process, as either of them could exist in the list you are matching to.
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