How to Maximise Trading During the Festive Season

Melissa UK Team | 2020, Data Audit, Data Cleansing, Data Quality, Ecommerce

The festive season is vastly creeping upon us, with Black Friday around the corner, retailers must turn their throughs to what will be their most profitable period – quarter 4.
In normal circumstances during Black Friday and even Cyber Monday, we would see a barrage of sale hungry consumers rushing around the high street taking advantage of their favourite brick and motor stores to an over surge of eCommerce sales.
Brands tend to now take advantage of the “whole” buying period by continuing promotions and discounts, encouraging further spending during Christmas, but even without the efforts, the traditional Christmas period as we all know is another busy time for retailers.

The stigma in your customer data

Marketing being a perfect example to driving these sales and promotions over the festive period must understand that although splitting their annual budgets and running rather extensive campaigns quarter to quarter, it’s common to see the highest spend leading up to Q4 to help maximise those profits leading up and during the festive season.

What we see as a stigma that tends to hold retailers back from obtaining higher sales growth is customer data they are working with. Generally having “fragmented” data as a common mishap. Which in turn can make these prolonged campaigns in the second half of the year less effective as they should be. This can be something to consider when giants like amazon are accounting for as much as 54.9% in sales during this period.

Retailers first must understand where their customers are interacting and engaging, which tends to widen over a selection of channels. These include website and online stores, apps, social media, customer service and technical departments right down to the actual physical brick and motor stores.

During engagement on these channels, customers and prospects will leave a diverse set of information, specific and pertinent, which trends on the individual’s activity over that channel. The issue is that multiple departments may be gathering this information which can cause confusion, duplication of records and inconsistencies over the whole customer life cycle.

Clean and verified data

Another issue that tends to bring retailers down is being able to obtain clean and verified contact data on their customers

There are two scenarios:

Customers onboarding and entering systems & databases

Typically, when they onboard into the organisation’s systems via purchase, registration, signup, enquiry, or any form of inputting their data

– Type the incorrect or misspelt information
– Missing information
– Formatting issues such as casing and standardisation
– Data in the wrong fields
– Same information but structured differently across various channels and systems
– Conflicting info (determining which one is right or wrong or both right)

Current Customer records going stale once entered into systems & databases

24% of database records go stale each year due to the following,

– Moving Address
– Changing status (eg married)
– Email
– Changing jobs
– Phone numbers
– Suppress/die
– DMA and preferences

Which is why it is equally as important to have clarity and consistency on your customer data so each department can deliver better results leading to overall increased revenue.

Data deduplication, matching & merging

While 24% of customer data can go stale over time, in our experience we also see that a further 10% of databases contain duplicated records, this is enough to impact the delivery of that single customer view every retailer strives for.

As well as seeing customers duplicating throughout departments and various systems in an organisation, this can lead to potentially seeing contacts as a new customer, another as a loyal customer, another as prospect which leads to confusion and potential for poor communication which is a waste on spending and risks alienating customers.

Enrich & enhance your data

When it comes to data, the more you get out of it, the more you can do with it – data enrichment and enhancement is a great way to truly understand your customers on various levels. Such variants like geolocation to pinpoint location, demographic and firmographic insight, IP location to missing contact information can not only give you improved targeting for better direct engagement but can find new customers just like your best ones.

Data audits and health checks

We recommend that all retailers have their data audited once every so often so they can get a clearer picture of the overall health of the data they are working with. This is great to identify any flaws and inefficiencies that may be causing issues which be now you should know, leads to further back draws to business success.


Retailers must understand that the accuracy of their customer data directly impacts any business activity downstream from reporting and analytics, segmentation and targeting, marketing all the way down to logistics, delivery, and customer care. So, if your data is inconsistent, everything is going to suffer.

Below is the data quality life cycle, Melissa can put in place for any retailer looking to achieve more. In doing so, the one aspect that every retailer strives for again is that single customer view or that one golden record that aggregates all the additional important information about a customer or prospect so you that all departments have a clear view and understanding of their overall journey with a retailer.

This in turn allows retailers to make sensible business decisions when communicating to their customers to give them an outstanding experience in the build-up to the festive season.



The Data Quality Life Cycle

Data Cleansing – What You Need to Know

Melissa UK Team | Address Quality, Clean Suite, Data Audit, Data Cleansing, E-Mail, Email Verification, Phone Verification

Today, organisations heavily rely on data for everyday business activities.
This makes data cleansing a critical requirement for anyone who has a database, so their organisation can yield better results across all operations.

Following are some core benefits of cleansing your data

1. A complete, accurate and real-time view on your database

Up to 30% of a database can go stale within a year, due to people changing address, jobs, emails, and simply updating their status. This causes data to become obsolete, which can lead to numerous problems which can spread through multiple departments and other data chains; impacting on marketing, engagement, business intelligence and overall business efforts.

By cleansing your database, you filter out any bad data in your systems to give a clearer view of prospects and customers.

2. Improved targeting for better conversion rates

As your database significantly improves so will your marketing efforts, as there’s no bounce backs from emails, or incorrect addresses to hamper communications with your prospects. Also, by matching and merging records you won’t be wasting time and money on sending out marketing material to stale and duplicate prospects.

And when you have clean reliable data you get a clearer picture of your customers, leading to better segmentation, and delivery of a single customer view.

3. Better ROI and saved costs

Consider the 1-10-100 rule, that it costs on average £1 to verify the accuracy of a record at point of entry, £10 if it needs to be cleaned and £100 if nothing is done – not including the cost of mis-deliveries of shipments, direct mail, missed opportunities and undetected fraud.

Businesses with clean, up to date and verified data on the other hand can expect to drive a standout customer journey, leading to better sales, cross and up-sell, and stronger revenue streams.

Which one would you prefer?

4. Positive brand value & reputation

A company will deliver and maintain better communications, and therefore reputation with its prospects, with clean data. It enables them to be more engaging across various channels, offer tailored promotions, speedy deliveries, and provide value across a range of systems and practices, such as at the point of sale. It also helps them to elevate customer retention efforts to meet the future customer expectations.

5. Putting together a data cleansing strategy

To achieve any of the above you must put together a data cleansing strategy. A great starting point is to analyse your data. Which departments are lacking the most clean data? Where is revenue being lost? And are there certain aspects of your database that are causing overlaying problems? It can sometimes be hard to spot issues, so take some time to do this.

Following is list of common problems a database can have:

  • Bad address data which causes mis-deliveries, logistical issues, and poor customer service
  • Fraudulent activity from not having a verified and up to date address, email and phone number, and its impact on delivering a single customer view
  • Duplicates in your database resulting in lower accuracy and wasted efforts and costs
  • Gaps in your data caused by incomplete records, like missing phone numbers, email, address and even IP
  • How standardised is your data? Punctuation & abbreviations must be in the right place i.e. in the spelling of emails or addresses, and always consider international formatting rules for postal regulations
  • Prevent a single customer view or 360-view of your customers
  • High bounce rates and blacklistings in your email campaign efforts

As the next step, we would recommend requesting a data audit from a data cleansing specialist. Ideally, it should be one that offers a complimentary service that really digs down on gaining vital insight on your data. Feedback should then be given on the ins and outs of the database, and advice on how to get the most out of it. Data quality solutions should also be recommended to implement into their current systems (see our data audit link above for more information).

Always remember that cleansing your database is not a one-off process. You should always be keeping tabs on your data, making sure it’s providing fulfilment at every point in the chain to save time and effort. It’s always best to take advantage of the SaaS services a data quality company like Melissa offers. Such a service ensures that your data is clean, verified and up to date as it enters your systems. It also automatically prevents your data from going stale each year, saving you money and giving back better ROI in the long term.

CRM Maintenance: A Step by Step Guide on How to Clean & Maintain your CRM Database

Melissa UK Team | CRM, Data Audit, Data Cleansing, Data Enhancement, Data Enrichment, Data Management, Data Matching, Data Quality, Data Quality Services, Deduping, Email Verification, Global Address Verification

As many of you know, a customer relationship management (CRM) platform is a vital part of the sales process, which entails keeping customers and prospects happy while moving them through the CRM pipeline. But many businesses forget the role CRM plays in the entire customer life cycle.

CRM platforms can be used for continuous communications with current and potential prospects and are playing a vital role across all sectors. In healthcare they can be used to gather and sync protected health information across multiple facilities, including providing post discharge follow-ups. For banks, they can be used to provide a better customer service across branches.

A big question is how can you keep track of all this data, whilst maintaining your ever-growing database and making sure your data is providing the insights your organisation needs to maximise its operations?

This step by step guide will unravel the practices you need to keep your CRM organised, pristine and maintained. It will draw attention to the common issues many databases have, including duplicates, misspellings, incomplete, outdated, unverified and unformatted data. We will also show you our recommended practices and tools, so that new data is entered into your systems properly and with confidence.

The Data Quality Life Cycle

Analyse Your Data

First and foremost, having an overview of your current data situation is critical when commencing data cleaning. Ask yourself how bad is our database? What are the common issues that we keep seeing in our database that’s reflecting on our business efforts and outcomes?  Some examples below.

  • Mis-deliveries of mail and products to logistical issues due to incorrect address data.
  • Duplicates throughout your database causing lower accuracy and preventing a clear view on your customers.
  • Incomplete or gaps in your data, like missing phone, email, address or even IP which can impact sales, marketing and business intelligence efforts.
  • How formatted does your data look in terms of punctuation & abbreviations i.e. misspelling of names, emails, CA for California, and international address formatting rules for global outreach?

Also, keep in mind that data will naturally degrade over time, as people move to a new house, change emails and phone numbers, leave companies and change job titles. Multiple data quality practices must be used to facilitate the above examples. Lucky for you we have the right guidance and tools to make it an easy process.

It’s time to clean up that CRM database!

As you now know, bad data comes in many shapes and sizes. There are various ways to clean it as well – let’s have a look at what we recommend: data cleanse & standardise, match & deduplication, data verification and complete missing data.


STEP 1: Data Cleanse & Standardisation

Bad data is largely caused by human error – such as incorrectly entered data. We recommend that your organisation should have some sort of standard in place to articulate how data is entered into your CRM systems. A great tool to provide this is a Data Cleanse software solution which can come in the cloud or API format, and easily integrates with your CRM platform. This will create an enforced & organised environment where consistent iterations of data can be entered into your CRM system.

The tool applies 5 main components to cleansing and keeping a consistent flow of entered data, including:

  • Punctuation – Adding or removing punctuation
  • Abbreviation – Correction of abbreviation (for example CHE for Chelsea)
  • Search & Replace – Search & Replace portions of a string
  • Expressions – Creating and programming automatic expressions to make sense of data values
  • Regex – Using regular expressions to extract and validate


Data Cleanse Interface


STEP 2: Duplicate Data & Matchup

In our experience, a database will contain almost 10% duplicate records, which results in inefficiencies and prevents you from achieving that single customer view. A common issue for businesses is keeping track of people in their database, changing names, status, addresses and so forth, which when obtaining their data from another source can cause this duplicate effect.

Our recommended solution, a Matchup & Deduplication tool, will allow you to identify, match records together, and eliminate duplicates.

There are 3 ways this tool can work depending on what you want to achieve in your database:

  1. Read/Write deduping

This will compare records in one or more databases at once, each unique group will be matched while the other matching records will be passed as “duplicates” this is best for businesses wanting to match and deduplicate entire databases at one time.

  1. Incremental Deduping

This is a great way to keep your list in tack of deduplicates having this tool running in the background as it compares each record to an existing database as fresh data enters your systems making sure of no duplicates.

  1. Hybrid Deduping

A combination of the above two methods but with the flexibility to personalise the process. Let’s say you have a small batch of potential matches; this will allow you to match it against incoming data or records. This is best for batch processing of entire lists while incurring real-time data entry


Data Match & Deduplication Interface


STEP 3: Data Verification

Next on up, we have data verification, we see this being as a very crucial element to your data making sure it’s clean, up to date and ready for use!

To put it simply, this is the process where your data is checked for accuracy and inconsistencies, determining whether data is complete, correct and accurately translated from one source to another. You want your data to be able to support any new processes in any new system.

There are several solutions that we recommend that will entail this, depending on which element of data want to verify, See below;


–             Address Verification:

From our experience, this is the most popular verification solution, as having correct and verified address data is a necessity for most business activities.

The way this solution works is it corrects, cleans, standardises and will add missing components to any international address and will format the address to the postal specifications of each country. This solution will also enrich your data by adding latitude and longitude coordinates to any address.

Our Address Verification tool can be integrated into almost any platform.


Address Verification Process


–             Name Verification:

This solution works best if your wanting to verify valid individuals or companies in a field. This process works by ensuring accurate gender determination, splitting multiple names into their correct components (title, first, middle, last and suffix), add casting for company names, and flagging any fake or vulgar names to reduce the impact of fraud and waste.


Name Verification Process


–             Email Verification:

A handy tool to verify emails – making sure they are active and can receive mail, which ensures successful delivery and reduces any chances of fraudulent activity or fake emails. This tool corrects typos and invalid characters, so only valid emails enter your system as well as ensuring SPAM compliance with mobile domain detection.

Email Verification Process


–             Phone Verification:

Lastly, this tool enables businesses to verify and correct phone numbers at the point of entry, ensuring that only valid phone numbers enter your database and that they are live and callable. Phone verification can establish what region / international location of a number, making it easier to determine the dominant language in that area.


Phone Verification CRM Maintenance


STEP 4: Complete Missing Data

Once your data has been cleansed and verified it’s time to enhance it. Complete the full data quality life cycle with a Data Enrichment & Append solution.

You want to get the most out of your data. The more you get out of it, the more you can do with it, making it an increasingly valuable asset. Without this option you limit the potential of gaining a 360-degree view of contacts which can lead to wasted efforts.  See the benefits of the Data Enrichment & Append solution below:

Further customer insight by adding: Global Geographic, IP Location, Business Firmographic, Demographic & Missing contact information like Name, Phone number, address etc.

Increase Response & Engagement: Understanding your customers and prospects on a deeper level allows you to communicate with them more effectively.

Better Targeting: Group your prospects by similarities, whether it’s by area, demographic or lifestyle you can attend to your market with an enhanced approach.

Maximise Effort: When updating any contact information weather its name, address, phone number or email, will allow you to reach your customers at the right time and the right way.

IP Location Example

IP Location Process

Business Firmographic Example

Business Firmographic Data Enrichment Flow


(Refer to for further detail & examples of data enhancement solutions)

STEP 5: Protect Your Data

To conclude this step by step guide we leave you with the most important element and that’s protecting your data! As customers in your database continuously update their status, address, phone numbers and so forth… it’s up to you as an organisation to keep track of this. Have a strategy in place that successfully allows you to implement the data quality life cycle, so that you always accomplish the best from your CRM.

This article has been produced for you by Melissa, your data quality experts, with over 30 years of experience we pride ourselves on being your one-stop-shop for all your data quality needs. – For help with a CRM maintenance strategy contact us today to achieve more.

Melissa feiert 35 Jahre in der Datenqualität

Melissa DE Team | 2020, Big Data, Data Audit, Data Cleansing, Data Management, Data Quality, Data Quality Assessment, Data Quality Services, Datenqualität, Ecommerce, Germany, Global Business, Global Data Quality, Press Release, Presseberichte | , , , , , , , , , , , , , , , , , , ,

Fachwissen und Technologiekompetenz festigen globale Rolle bei der Verbesserung von Daten für Analytics, CRM, Handel und Compliance

Köln. Melissa, ein führender Anbieter von globalen Lösungen zur Adress-, Namens-, E-Mail-, Telefon- und Identitätsprüfung, feiert sein 35-jähriges Firmenjubiläum. Das lange Bestehen von Melissa ist auf jahrzehntelange Expertise in allen Fragen rund um Adressen und umfassendes Fachwissen, das die Grundlage für globale Intelligenz bildet, zurückzuführen – alles aus demografischen, geschäftlichen, standortbasierten- und Identitätsdaten. Dies ist die Basis, die Unternehmen ein umfassendes Risikomanagement, datengesteuertes Engagement, Analysen, Einblicke und Compliance ermöglicht.

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