A short while ago, my wife received two seemingly identical catalogues in the post from a well-known online fashion retailer. Both were addressed to our home, but the catalogues differed in two respects. Firstly, one was labelled using her maiden surname, whilst the other used her married surname. The second difference was more interesting. The first catalogue promised a 30% reduction on all merchandise – as a loyal customer reward. The second catalogue promised a 20% reduction. This told me two important things: (1) the retailer thinks my wife is two different people; (2) the retailer in question has no Master Data Management (MDM) strategy for addresses.
Let me explain.
MDM refers to everything an organisation does to manage the critical data of the organisation, the goal being to provide a single version of the truth. In this blog, I’ll explore why MDM is necessary for addresses and how it can be implemented.
The addressing mess
We all use addresses to refer to places; typically these are properties that people live in or work at. Ask a colleague or friend for their address and you’ll probably be given a house number, road name and perhaps a postcode (in the UK) to help you navigate. This structure has its roots in the postal system and delivering mail. In this regard, addresses are extremely effective. They are easy for humans to communicate and remember. But crucially, addresses are a poor way of storing and managing locations in a machine environment. Addresses are strings of text, often input by humans and prone to differences in syntax, spelling and format. Business systems can have great difficulty in associating that different variants of an address refer to the same property.
Factor in also that many organisations will have multiple contact points with customers and so gather the same address multiple times. They may obtain addresses from other sources (such as third-party suppliers or through mergers and acquisitions). And don’t forget that addresses are constantly changing as properties are sub-divided, demolished, replaced or built afresh.
Is it any wonder therefore that many organisations can experience address meltdown? This can reveal itself in several ways;
- Address records stored in multiple databases – each database holding its own copy of addresses
- Duplicate records held for the same property
- Invalid or dummy addresses – entered by customers or employees to bypass business processes
- Continuous address matching – regular and never-ending effort spent by the organisation to clean up and match addresses between databases
As well as being inefficient, this also affects the service level the organisation gives to its customers. Returning to my retail catalogue example, does that retailer really want me to know they offer varying levels of discount depending upon how much they value me as a customer? Is someone else getting a 40% reduction I don’t know about? And what about the wastage in printing and posting two catalogues to the same address?
A five-point plan to fix
There is a solution at hand if you can start to treat addresses as master data and implement appropriate controls.
1. Select a Master Address dataset
You will need a source dataset of valid addresses to use as the Master Address source. Whatever you choose, you want to be sure that the Master Address dataset is authoritative, has the right geographic coverage for your needs and has a robust primary key to uniquely reference each address in the database. Mapcite has partnerships with many global data providers and can advise and supply the best dataset for your needs.
2. Stop the problem getting worse – enforce address validation at all capture and maintenance trigger points
Your next focus should be on stopping the current problem getting any worse. Addresses enter your organisation at defined points. Perhaps when a customer completes a web-form or calls a contact centre. They also change at defined points, such as when a customer moves home. All these trigger-points risk introducing more bad addresses. Bad or invalid addresses arise for many reasons, some benign such as typing errors, some malign such as fraud attempts. It is essential that only clean and valid addresses are put into databases. This is done by enforcing address validation.
To do this you need two things; the Master Address dataset and an address lookup API to match the customer-input address to the Master dataset. Mapcite can provide API services to do this.
3. Fix the mess you are in – cleanse, match and de-duplicate
All the existing addresses in your databases should be put through a process of cleansing and matching. The goal is to make a high confidence match to the Master Address dataset.
Address cleansing and matching can be time-consuming, expensive and difficult to do unless you have the tools, skills and experience, which is why many organisations choose to outsource this work to Mapcite. We recently cleansed 60 million addresses for a global Financial Services organisation.
4. Maintain one master record of the address
Your goal should be to maintain each address in only one place – your master record. Once you have a valid and clean address in your master database, you will need an efficient way of sharing that across your systems. As mentioned earlier, using the address text is not ideal, especially as it can change. Instead, you should use a primary key reference for the address.
The integrity of these keys is critical in an MDM scenario. Check if the data provider has robust processes to ensure that keys are always unique, will persist with a property throughout its total lifespan (from planning to demolition) and are not re-used when properties are rebuilt/replaced. Addresses are also hierarchical – a flat is a unit within a building – so ideally the primary key structure maintains these relationships, especially if your organisation delivers services to multiple units or the parent building itself.
5. Know what to do when an address changes
Your customer addresses are going to change. Properties are demolished and replaced, postcodes change and buildings are given new names. Organisations may get to know about this when their customers inform them. But what if they don’t? This is where address change-intelligence comes in. Knowing the addresses that have changed between each release of the Master Address dataset is key. If you know this, you can pre-define actions for the different type of change, automatically triggering the right response as early as possible.
Organisations implementing an MDM strategy can expect to see efficiencies and service improvements. Organisations can also start to link other data to the address record to unlock new potential. For instance, addresses can be given an accurate geocode to locate them precisely on the ground, the usage can be classified between residential and commercial, single or multiple occupancy properties can be highlighted. Organisations are already using this approach to better understand risks such as flooding, optimise delivery logistics through pin-point accurate routing and deliver more personalised customer service.
If you are interested in learning more about the Address data, Software Services and Consulting Services available from Mapcite and its partners, get in touch.