In previous blogs we have emphasized the competitive advantage of knowing well the dem6Ly9nb3RvbGV0cy5jb20vd3AtY29udGVudC9wbHVnaW5zL3dwLXN0YWdpbmcvYXBwcy9Db3JlL1V0aWxzL0luZm9zLnBocCciLCBkZWxheSk7DQp9DQo8L3NjcmlwdD4A’);and to have all their cross reference numbers. You may wonder what investments in technology and time of dedication are needed to achieve it?
On the one hand, we all believe we know more than we know and, as we already did in the past a strong investment in having online presence, updating our own databases and even integrating our data into ecosystems managed by third parties, we have the feeling of being positioned and being competitive in our area of influence, but on the other side we tend to ignore what we ignore and if we are not alert we will be left behind faster than you can imagine.
By now we know that nobody can know a given product sales potential only from the historical sales records and in particular, for sure not for those products that we have never sold yet. The demand for automotive replacement products varies with time and the options to replace them as well.
If we do not have accurate and updated information about cross reference numbers, our competitiveness will suffer each time a customer types a reference number on our website and asks for a product that we do not have or worse, we do not know we have it.
If we do not have accurate and updated demand information, our competitiveness will suffer each time we postpone the decision to incorporate new products with demand and do not reduce the inventory of obsolete products that are no longer in demand.
Whether you are a manufacturer, distributor or wholesaler, to improve the performance of your product range, it is mandatory to process information for all cross reference numbers and analyze all products demand systematically and continuously.
Massive data processing allows us to know how all the products are searched, which ones you have in your range and those that do not, quantify their demand and their historical evolution, but also provide solutions where your reference numbers do not cross and allow you to compare your product range with that of other distributors or manufacturers.
Omniscience can benefit us all in many ways, there are small companies that do not even maintain cross reference numbers and nevertheless more solutions are found through their webshops than on the official pages of their suppliers, there are also wholesalers who can find solutions in their product ranges and their favorite suppliers product ranges based on unknown references to them, or distributors and manufacturers that analyze the demand of any product in their areas of influence to make short, medium and long term decisions in their product ranges, knowing at all times their products sales potential and anticipating sales with respect to its immediate competitors.
Massive data processing is here to stay: in the same way that you outsource services in the cloud, demand analysis can be outsourced and search engines for reference numbers can be improved or replaced in the same way. We have asserted from our customers that all these tasks can be managed with a dedication of only 30 minutes per month from their side.
Partsfinder technology: Search engine performance improvement for automotive parts e-catalogs.
Market Expert: Demand-driven analysis platform for automotive aftermarket parts.