Data is at the heart of the modern retail industry. Ensuring all the data a retailer has are integrated and spotlessly clean is no easy task but nowadays goes much more smoothly with Spotless Data's API solution.
Data have been described as having taken over the retail industry due to the profound impact they have on every area of retailing. They are changing the way we buy and sell products, and not only in online retailing but more traditional offline retailing as well. Those retailers who are putting data first by ensuring all the data in their repository have data integration, by using data-driven approaches to retailing, are emerging as the new winners, whether this is a large multinational corporation or a local corner shop. and allowing your retail business to have
The most far-reaching visions imagine a world of retailing dominated by the Internet of Things where customers will rarely make a purchase as routine acquisitions will be fully automated, whether it is the weekly supermarket shop or a pint of milk delivered from the local convenience store. Predicting trends, in order to be able to offer the customer what they want, is also of increasing importance, whether these are things people buy daily, the latest fashion accessories or presents people buy to give others at Christmas and similar holiday festivals, where demand can increase hugely compared to the rest of the year. And this data is enormously varied so that a retailer in umbrellas or sunglasses will undoubtedly want to know what this week's weather is going to bring, a classic example of third party data which doesn't appear to have anything to do with retailing.
One of the thing which drives modern retailers is using data to understand their customers better so that they can attract more of them and drive higher sales. Many retailers thus look to analytics software to help them both understand and use the data they have to help streamline their businesses and offer greater customer satisfaction. However, as many retailers have already found to their cost, trying to gain meaningful insights or anything useful whatsoever out of rogue data, which are full of inaccuracies and inconsistencies, is well-nigh impossible. The reality is that, dealing with big data, as modern retailers need to do, that unless the data have been given a thorough data cleaning to guarantee that they are trustworthy and have data quality, that they will not be of any use, and indeed can be a positive menace to retailers. This, though, is not a reason to reject the idea of using data in retailing, even for the smallest retailers such as corner shops. Rogue data may be worse than no data, but clean data are much better and more effective than either.
Fortunately, there is now a solution in Spotless Data's machine learning filters, which have been designed specifically and solely to clean your data. This ensures that every last piece of data has data validation that will then allow your analytics software to work as it should rather than being plagued with problems, nulls and errors because the software cannot draw accurate conclusions from rogue data.
The most common data which are used by retailers are those found in customer relationship management systems, which uses the data, including historical information, about both actual and potential customers to maximise customer retention, and enterprise resource planning systems, which contain the data about core business processes. It is only by combining CRM (such as single customer views) with ERP that one can gain a fully 360-degree view of one's customers, enable real-time access for your staff to all the data and the streamlining all the business processes to ensure cost-effectiveness, speedy responses and no wasted effort. All this without impeding the all-important customer satisfaction.
However, reconciling these two different types of systems is never going to be easy unless the data are impeccably clean and consistent. The Spotless solution is our data validation API which allows retailers to clean and validate all the data through a web browser. Spotless initially offers a report based on what our automated systems believe is the best way to clean your data once they have analysed them to spot any potentially dirty data and then allowing the customer to set the specifications which will clean the data themselves. Do sign-up for our service and take a look to see how well we spot the inconsistencies and inaccuracies in your data.
Integrating third-party feeds is always a tricky process, partly due to variety within the meta tags used to describe these data and partly due to inconsistencies in naming conventions so one database may talk about "milk" while another may talk about "full-cream milk", "semi-skimmed milk", "skimmed milk" etc. The important thing is not what a product is called but consistency so that a particular product should always be given the same name within the retailer's database. This is normally easy with structured data which comes from the retailer itself but when it comes to data from third-party sources, and unstructured data generally, naming consistency is unlikely to be found within the crude data. The digital systems needs to know that "milk" and "full cream milk" are the same thing (assuming that within your repository they should be the same thing) or it will get confused and give poor quality analysis that will almost certainly be worse than no analysis at all, because it gives misleading information.
Marketing databases can gather together a great deal of information from third party sources which can truly ensure that the latest marketing campaigns are a great success with customers while defining real objectives whose achievement can be measured. And when using a sophisticated analytics software to generate business intelligence, the more data that the marketing team can gather into their database, including dark data such as the IP location of those using their website, the better the results are likely to be. However, this is only so when the data have been properly scrubbed up so that the analytics software cannot merely make head or tale of them but extract the maximum amount of intelligence from them.
You can read our introduction to using our API and then try out our service on your My Filters page but, for this, you need to log in first. If you haven't already done so, you can sign-up using your email address, Facebook, Google or GitHub accounts. You may also view our video on data cleaning an EPG file, which also explains how to use our API.
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If your data quality is an issue or you know that you have known sources of dirty data but your files are just too big, and the problems too numerous to be able to fix manually please do log in and try now