When it comes to managing Big Data, it’s hard to picture a solution that can effectively manage the massive quantities and variations of customer and business data, much less in a way that actually alleviates stress instead of compounding it.
Yet while complex, those endless tables of alphanumeric information contain key data points that, when properly joined and identified, can reveal the kind of trends, patterns, and insights that drive nearly limitless revenue.
To truly harness this revenue, the accuracy of that data must be matched by its accessibility. Translation: your customer data is only as strong as your employee’s access to it. Consolidating various touchpoints into one database allows employees to see an entire customer journey and deliver a more personalized experience.
Therefore, a reliable, investment-worthy solution should include a fast and accessible way for users across the business to work confidently with their data. But what else goes into data matching software? So you can feel confident about the software you invest in, ask potential data matching partners the below questions – and be wary of anyone who is hesitant to give you a thorough answer.
Considerations for Evaluating Data Matching Solutions
Let’s dive into the top eight questions we frequently hear from customers regarding data matching:
1. Is the software able to ingest any data source while still analyzing the data accurately?
The most effective solution will not only perform out of the box but will also be adaptable and expand to incorporate any format of data, regardless of your brand or industry.
Comprehensive analysis of customer or business data, including names, addresses, phone numbers, and contact information no matter the country, should be able to ingest a variety of data. Consider all your customer touchpoints in order to create a 360-view: documents, web pages, databases, and all social media will need to be considered.
2. How many languages is the software able to transliterate and match at scale?
The most reliable results can only come through broad multi-language capability. Ask particularly for transliteration expertise when it comes to challenging languages (i.e. Arabic, Chinese, Korean, Russian – even Klingon!) and how they are considered.
3. How thoroughly does the data matching solution consider possible record matches?
You want a product able to identify possible matches by the same means that humans do – contextually - but at a superhuman scale. A truly intelligent solution should consider names, nicknames, initials, as well as any possible misspellings, typos, or misalignment – regardless of language, table schema, or where it resides within that table.
4. Does the data matching solution rate the reliability of each potential record match?
The most useful and thorough data matching solutions for party and non-party data not only include powerful defaults but also allow for customized analysis of your data via click-or-code configuration settings. Users can easily set custom match rates, weights, and thresholds, allowing for multiple passes to quickly fine-tune the matching process for your needs while rating the accuracy of your matches.
5. Can the matching software identify links between records with phonetic typos – like knowing the difference between “Knotten” and “Naughton”?
Data matching solutions should interpret records contextually so they can connect the right record to the real-world people and things they represent- even while taking into account phonetic variations and possible misspellings of the same name.
6. If my needs require multiple products or software integrations, do they work together – and how?
A suite of products designed to seamlessly integrate is more likely to provide greater synergy and consistency, and higher quality analytics than if you combine standalone products.
7. Are there customization options that can be easily scaled with growing customer data over time?
The most responsive and cost-effective solution will meet your immediate needs, add additional features as required; grow with your future needs; and handle massive and complex datasets with efficiency and accuracy.
8. How does the matching solution fit into my existing infrastructure?
Account for future growth by investing in modular data quality platforms or matching solutions that fit into existing core systems to provide flexibility and scalability. Look for data matching software that can be layered onto existing infrastructure, whether it be on-prem, in the cloud, or a hybrid of the two. Most legacy software solutions weren’t built to talk to modern cloud-native technologies, but the right data matching and data quality platform can bridge the communication gap between old and new systems.
Finding the Best Data Solution for Your Business
No matter what you land on, remember: be cautious, demanding, and ready.
This software is going to be in charge of cleaning and deduplicating your company’s most valuable resource – its data! Take your time, be cautious, discerning, and make sure the partner you choose understands your unique use case and isn’t over-promising something they can’t deliver on.
This is where part two comes into play: be demanding. When it comes to your data, it’s okay to hold potential software to a higher set of standards. Ask questions and take the platform to task. Now that you know what’s possible, don’t be talked into settling for less.
Last but not least, be ready. Nothing is worse than spending the time and investment on software only to outgrow it in a year. If you go about it right, the right solution could be the last data quality platform you ever need to onboard, so make sure scalability and interoperability are baked in.
Ready to learn more about Syniti's enterprise-grade, AI driven data matching solution? Learn more here.