In recent years, demand has greatly increased for rich and accurate product data to populate eCommerce websites, aiming to drive customer and product experience and thus generate increased sales. This is an obvious trend, and many companies already have sophisticated UX setups in place to reap up the benefits of relevant data they offer to their customers. What is not really obvious to everybody at this stage, is what is going to be the next big thing in eCommerce and how it will affect the way companies manage their product data.
At Allium we believe that buying and selling products and services online will become more and more of an automated thing during the current decade, done by smart machines working for humans. Voice searches will also have an increased share of information look-ups on the web. To stay on top of the game, your data must be clear, precise and readily available to take advantage of these new smart channels. For sure that cannot be done by cohorts of people manually scouring at features for many thousands of items in Excel files.
Maybe data quality has never been a priority for your organisation. Or perhaps your data quality has been reasonably good for print, but it’s not in step with the evolving demands of eCommerce across mobile platforms or across the new evolving channels.
Whether you only produce printed catalogues for your customers, or whether you sell online and your information will be seen by humans or the Google Assistant, one thing is for sure: you will have to present your products well to sell well. PIM becomes a must-have for more reasons than one, but especially for data quality reasons.
Please find below the usual suspects causing data quality issues in companies of all sizes, and the way using a PIM such as Pimics helps alleviate those issues.
1. Missing data
Most of the time, a product’s information must contain a minimal set of details to meet criteria for publication in a customer-facing medium such as a printed catalogue or an online shop. Amazon for example, has very clear rules about the minimal set of details for a published product to qualify for displaying in their marketplace.
Possible such details include product dimensions, product color, product description, translations in the case of multi-language environments, etc. Also, there can be details which are not mandatory but would be nice to have, so it would be great if your software would remind you about those details when you try to validate an item for publication.
Standardizing this minimal set of data for each item in the company’s product range can be very difficult if not using a PIM. On the other hand, this is very easy to do when using a PIM software, as data checking is one of its primary features. Pimics is particularly good at defining such standard data at a field level as mandatory or optional, using checklists with sophisticated customization options.
PIM standard features like data inheritance also play an important part when making sure your product catalogue is not missing any data, automatically filling in common data for categories of products. As such, a common feature for a whole category must be specified just once and it will be automatically replicated to all inheriting entities for that category. A lot less work, a much more reliable dataset.
2. Data accuracy and consistency
A PIM system enables data standardization on a number of fronts. Be it units of measure or feature values, PIM enables you to have consistent descriptions for your products so that your product data doesn’t read ‘l’, ‘liters’, ‘Liters’ or ‘lt.’ in different contexts for the same unit of measure, or maybe ‘yellow’, ‘YELLOW’or ‘Yellow’ for various items having the same color.
Of course, in many cases PIM data are entered manually so data accuracy issues are still possible, but they are mostly avoided by using bulk imports from vendor data files, and by using the standardization features enabled by the PIM. Again of great help for data accuracy and consistency is the inheritance of product features, which enables less work and less human error when shaping and enriching your product data.
Limiting manual work on product data also limits unwanted data duplications. Having a rigorous structure in your PIM and a well thought-out product tree will prevent this from happening.
Sometimes even using automation, data duplications could be caused by errors in the import file, because from a fault on the vendor’s side there can be for example two differently named descriptions referring to the same product feature. A good PIM software will be able to detect such issues when they arise, and warn the user about it, or act according to a pre-set rule. Pimics can be set to recognize such possible problems and treat them accordingly.
In other instances, a degree of data duplication is desirable, for example in setting certain descriptions for items and item categories, and Pimics has the flexibility to allow you to do that too.
4. Outdated information
The easy bulk data imports from vendors enabled by Pimics ensure that you will always have up-to-date information about your products. Inheritance will play a role here too, because automated data propagation by inheritance means fresh data is always where it should be, and all concerned items will be touched by an information refresh.
Your sales channels will be updated in a timely manner with every product data change, because Pimics allows full automatic update for all sales channels.
5. Too many hands in the pie
When you keep your product data in Excel files in scattered places, it is very hard to control who has the right to do what. It is not uncommon in such situations to have data inconsistencies caused by people who inadvertently make the wrong modifications, or make the right modifications in the wrong places.
Having granular control over what each user can/must do in a centralised product catalog controlled by PIM, can do wonders to the level of trust your company will have in its own product data. Pimics specifically offers an easy way to control user rights, extending the default ERP rights with its own, PIM-specific user settings.