The Role of Data Quality for Charities

Melissa UK Team | Address Check, Address Correction, Address Quality, Address Verification, Analyzing Data, Analyzing Data Quality, Big Data, Data Management, Data Matching, Data Profiling, Data Quality, Data Quality Assessment, United Kingdom

2% of contact data is subject to inaccuracies every month which means that almost 25% of data is corrupted on an annual basis. However, new statistics demonstrate that organisations find almost 30% of their contact data to be inaccurate.

This is not an alarming statistic as smart technology has meant that we are more connected than ever, but it has created distance between organisations and clients. Charities and not-for-profit organisations also fall victim to the distance created by growing technology and in order to create a smooth experience for supporters as well as to gain trust and loyalty, good quality contact data is needed.

Creating a process for good quality contact data is not actually difficult. Charities and not-for-profit organisations can implement software which cleanses their existing data, removes duplicates and standardises the data held whilst providing real-time verification of data to ensure quality data enters into the newly cleansed databased.

Melissa work with a number of not-for-profit organisations to help them maintain a strong contact database – our previous experience has shown us that a quality database is key to marketing and raising support for their work. Our solutions which including data matching, deduplication and data cleansing has enabled a number of charitable bodies to increase their outreach efforts and enhance their fundraising efforts.

Enhancing data quality plays a strong role in creating a solid reputation and seamless supporter experience. Reputation and experience are key drivers of support for not-for-profit organisations and charities and so with the right contact data, engagement with supporters is not lost and contact is made to the right people, at the right time, with the right message.

Good quality data also has an impact on the day-to-day operations as it can reduce costs in the long run. Charities and not-for-profit organisations come into contact with large numbers of data and manually sorting this data can be time consuming and costly – having a data quality solution embedded into the database will not only reduce time spent on sorting data but provides cost efficiencies that can invested elsewhere within the organisation.

It is also important to note that regulation plays a huge role in today’s digital society. Regulation regarding privacy and protection can become more difficult to meet as the volume of data grows however, with a data quality solution, keeping contact data up-to-date is no longer an issue. Management are able to focus on other areas of the business as the solution ensures compliance requirements are met including GDPR.

Finally, tackling data quality issues allows for charities and not-for-profit organisations to become part of the digital world. It opens the organisations up to future technological changes which can further enhance the supporter experience and raise awareness for the organisation’s work.

With solutions which can be embedded anywhere within an organisation’s process, Melissa works with their clients to create a data driven competitive advantage. Using our tools, you’ll be getting the most out of your data which could be key to your future growth and success. Today’s digital world means that there are high expectations and charities, just as much as financial institutions, are expected to meet the technical expectations of consumers.

Melissa are also proud to be part of HM G-Cloud 10 framework – we work with a number of public sector bodies and offer a special rate for registered charities. If you would like more information then please give us a call on 020 7718 0070, or email us at

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When does Big Data become Bad Data?

Melissa UK Team | Analyzing Data, Analyzing Data Quality, Article, Data Audit, Data Cleansing, Data Enhancement, Data Enrichment, Data Governance, Data Integration, Data Management, Data Matching, Data Migration, Data Profiling, Data Quality, Data Quality Services, Express Entry, FinTech, GDPR, Global Address Verification, Global Data Quality, Global ID Verification, Global Name, Global Phone Verification, International Address Verification, United Kingdom

Last month, we spoke about big data and the importance of leveraging such data to provide insights to drive better informed business decisions. But at what point does this data become useless?

As we mentioned, big data provides detailed insight as it draws upon information from a number of sources and data points and thus, big data can reveal new opportunities, insights on customer behaviour and forecast changes in the industry, all of which will help an organisation’s success. Nevertheless, this data can turn sour and it is important that firms are able to leverage big data before it comes into bad data.

How do we prevent big data becoming sour?

There is no recipe into preventing big data becoming useless because eventually the value of data will expire as the industry grows and customer preferences change. What firms can do, however, is stay on top of their data by preventing bad data entering into their systems and analysing their big data in a timely manner.

Collection of data is important but gathering too much data can lead to the collection of bad data, which will crowd databases. Staying on top of data refers to firms prioritising the data that they collect and being able to streamline and analyse this data using a clear and concise data strategy. It is also important that data is analysed in a timely manner – research shows that over the year, 25% of data becomes inaccurate due to various reasons and so firms should actively seek to use their data to provide insight as soon as they can.

The majority of bad data comes from the fact that firms are dealing with more and more data but not verifying such data. As organisations are capturing more data than ever, the likely chance of this data capture being unorganised is higher than ever. Unorganised data is linked to unverified and unstructured data which is much harder to analyse and use for customer insights. It also creates a lot of time wastage as data analysts are forced to restructure such data before the data can be properly used. This data is thus bad data and prevents the ability for big data to drive customer success.

Where do we start?

Good data has the ability to drive success and in order to generate good data from big data, firms need to ask the right questions. What data do we hold? Is this data accurate and up to date? Has this data been verified? The underlying data that organisations already hold can be the cause of bad data and so firms need to address this before they can look to using their data for insights and business decisions.

The solution to this is similar – a tailored data quality solution which helps to monitor data that is already held as well as new data captured. Interested in finding out more? You can speak to the team on 020 7718 0070 or via email at

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The Generation of the mobile phone

Melissa UK Team | Analyzing Data, Article, Clean Suite, CRM, Data Cleansing, Data Enhancement, Data Quality, United Kingdom | , , , ,

Mobile phones sales have been increasing year in year out and the number of mobile users is expected to surpass five billion by 2019. It was estimated that approximately 63% of the world population owned a mobile phone in 2016 and this number is due to increase to 67% in 2019.

This growth in mobile phone ownership demonstrates the need for organisations to optimise the customer’s mobile experience. A user’s mobile experience is linked to their customer experience and if firms are not able to optimise their mobile experiences, they could be subject to lower conversion rates and diminishing returns leading to a negative customer experience. But how do firms optimise their mobile experience beyond the development of an app or a website redesign?

Verify, cleanse and monitor data

The mobile experience plays a strong role in the customer experience and inaccurate data contributes to a negative customer experience – this is due to human error which creates data errors. By investing in data quality tools that will verify, cleanse and monitor your data, your organisation will be able to prevent and reduce human error. These tools can work in real time or used in batch processing which will help organisations prevent inaccurate data from entering their systems and reduce errors in data that is already in the system.

The tools can also be used to analyse data helping firms to properly manage their data – data provides customer insight and when properly managed will help to inform business decisions, drive business performance and aid business growth.

Prevent duplicate data by using auto-complete forms

When thinking about the mobile experience or how seamless and convenient a website or app is, what comes to mind is the number of keystrokes needed to enter information. Using a verification tool can help to validate information as it is entered removing the potential of duplicate entry and so creates a more seamless mobile experience.

The experience could be further upgraded by using auto-complete forms such as address autocomplete whereby the system will suggest potential addresses based on the entry of a few characters. This will not only reduce key strokes but also reduce potential human error.

Data matching

Accurate data is linked to having the correct contact data for all clients but also being able to match data to a single client. By linking data from across different systems and assigning it to a single record, firms are able to build a strong foundation of good quality data which can be used to personalise the mobile experience. Data matching prevents duplicate entries from the same individual but also helps to enrich data which will help to strengthen the quality of databases.

Having a single customer view allows for firms to personalise experiences which enhances the customer experience but also informs key business decisions such as discounts and offers.

From here, we can see that data quality plays a key role in the mobile experience and it allows organisations to upgrade this experience for users as well as tailor it to individual users. As mobile ownership continues to grow, optimising the experience is important for the customer experience as well as the success of an organisation.

Melissa offers a whole range of data quality solutions that can be tailored to your business needs. If you’re interested in finding out more about how we can help you, please get in contact at and we’ll be happy to schedule a demo as well as a free trial.

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What’s all the fuss about Big Data?

Melissa UK Team | Analyzing Data, Analyzing Data Quality, Big Data, Data Audit, Data Cleansing, Data Quality, Data Quality Services, United Kingdom | , , , ,

According to data analytics company SAS, big data is a term used to describe large volumes of data, whether structured or unstructured, that businesses deal with on a daily basis. Big data can be broken down into the three Vs:

  • Volume: businesses collect data from various sources and with increasing use of the internet and social platforms, there is more data available than ever.
  • Velocity: locating data can be now easily and rapidly done but it is expected to be dealt with in a timely manner.
  • Variety: data can come in several formats from structured data in the form of numerical data to unstructured data in the form of emails and financial transactions which can impact the complexity of data for a firm.

With this being said, firms are expected to link, match, cleanse and enrich their data to share throughout the organisation. But increasing volumes, velocities and varieties of data mean that data can quickly become complex and control of data is lost. Organisations need to create a system which help them collect, store and analyse data in order to benefit fully from the advantages that big data brings.

Before firms look to see how big data impacts their business, it is important to note where data comes from. There are three categories:

  • Streaming data: this refers to data that reaches your IT systems from connected devices in which you are able to analyse almost immediately to determine whether it should be kept, discarded or put aside for further analysis.
  • Social media data: social platforms are providing more and more information and as it tends to come in unstructured forms, it can be difficult for firms to analyse.
  • Publicly available sources: data is available through open data sources such as portals that belong to the government and these tend to come in structured forms.

Statistics report that only a small percentage of data is actually analysed meaning that data that is collected and stored remains useless. Having too much data is not necessarily a bad thing but it is how this data is managed and handled which is most important. Taking raw data from any source and analysing it will reduce costs related to data, optimise time spent on business decisions and enable better product development to suit customer preferences and needs.

When big data is analysed, it has the ability to provide insights which will enhance business decisions as better informed decisions come from the confidence of using knowledge which comes from data.

Use of data analytic tools with big data can enhance how businesses perceive and use their data allowing for tasks such as determining problems with data, detecting fraudulent behaviour ahead of time and understanding consumer behaviour to be easily done. Firms can consider different types of ways to manage and handle their data such as processors, open source data platforms and cloud services to help them get to grips with their data.

To find out how Melissa can help you manage big data, contact or ring us on: 020 7718 0070.

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