In the UK this Christmas, the most successful retailers have been those that sell online but allow collection by the shopper – in fact, these companies have represented a large proportion of the retailers that had a good festive season. One innovation has been the rise of online retailers paying convenience stores to take delivery and provide a convenient collection point for the shopper, but two of the country’s biggest retailers, John Lewis and Next, reckon that click and collect has been the key to their Christmas sales figures – and of course they both have high volume e-commerce sites as well as many bricks and mortar stores.
The article here by the Daily Telegraph explains why “click and collect” is proving so popular, especially in a holiday period. The opportunities for major retailers are obvious, especially as they search for ways to respond to the Amazon threat – but how do they encourage their customers to shop online and also promote in store shopping? The key is successful data-driven marketing: know your customer, incentivize them to use loyalty programs and target them with relevant offers. However, this also presents a big challenge – the disparity and inconsistency in the data that the customer provides when they shop in these different places.
In store, they may not provide any information, or they may provide name and phone number, or they may use a credit card and/or their loyalty card. Online they’ll provide name, email address and (if the item is being delivered), credit card details and their address. If they are collecting in store, they may just provide name and email address and pay on collection – and hopefully they’ll enter their loyalty card number, if they have one. To complicate matters further, people typically have multiple phone numbers (home, office, mobile), multiple addresses (home and office, especially if they have items delivered to their office) and even multiple email addresses. This can be a nightmare for the marketing and IT departments in successfully matching this disparate customer data in order to establish a Single Customer View. To do this, they need software that can fulfill multiple sophisticated requirements, including:
- Effective matching of customer records without being thrown off by data that is different or missing.
- Sophisticated fuzzy matching to allow for keying mistakes and inconsistencies between data input by sales representatives in store and in call centers, and customers online.
- The ability to recognize data that should be ignored – for example, the in-store purchase records where the rep keyed in the address of the store because the system demanded an address and they didn’t have time to ask for the customer’s address, or the customer didn’t want to provide it.
- Address verification using postal address files to ensure that when the customer does request delivery, the delivery address is valid – and even when they don’t request delivery, to assist the matching process by standardizing the address.
- The ability to match records (i) in real-time, in store or on the website (ii) off-line, record by record as orders are fed though for fulfillment and (iii) as a batch process, typically overnight as data from branches is fed through. The important point to note here is that the retailer needs to be able to use the same matching engine in all three matching modes, to ensure that inconsistencies in matching results don’t compromise the effectiveness of the processing.
- Effective grading of matches so that batch and off-line matching can be fully automated without missing lots of good matches or mismatching records. With effective grading of matching records, the business can choose to flag matches that aren’t good enough for automatic processing so they can be reviewed by users later.
- Recognition of garbage data, particularly data collected from the web site, to avoid it entering the marketing database and compromising its effectiveness.
- Often, multiple systems are used to handle the different types of purchase and fulfillment. The software must be able to connect to multiple databases storing customer data in different formats for the different systems
With a wide range of data quality solutions on the market, it’s often difficult to find a company that can check all of these boxes. That’s where helpIT systems comes in. If you are a multi-channel retailer currently facing these challenges, contact helpIT systems for a Free Data Analysis and an in depth look at how you can achieve a Single Customer View.