
Using software solutions in the car trade is no longer an insider tip. Calculation tools, vehicle exchanges, customer management systems - all of these have long been standard. But instead of a clearly structured system
A potential customer becomes a real customer when the search result meets his expectations. For this to happen, the search criteria must be carefully selected. Examples such as mobile.de and Co. show how this can work in practice, where a distinction is made between "rough" and "fine" searches. In the rough search, the user enters only a few particularly important criteria and looks at the results. If the number of matching models is too large, the search can be refined by the customer entering additional criteria. If, on the other hand, no suitable model is found in the hit list, the customer has the option of setting up e-mail notification when models matching his criteria appear. In this way, sooner or later the prospect will get the car of his or her dreams and turn a potential customer into a real customer. But this system can be improved.
The latest results of relevant studies show that some of the search criteria used on portals such as mobile.de and Co. in the "detailed search" search mask are not at all important for interested parties. For example, the latest studies show that it is not the number of seats or the presence of assistance systems that are important for refining the search, but rather the type of fuel, the mileage, the offer price and the vehicle location. On the other hand, the type of gearbox, the colour, etc. are of less than 20% interest to all potential customers. Therefore, in order to improve lead quality, the refinement of the search result should primarily be based on the first mentioned criteria. And for a rough search, such criteria as the make, model and age of the car are perfectly sufficient. The ideal division of the search masks into the coarse search mask and the fine search mask can be illustrated most clearly as follows:
Rough search mask:
Brand (94% of potential customers are interested according to mobile)
Model (83.3% of all potential customers) Vehicle
age (63.8% of all interested parties)
Fine Search Mask:
Fuel type (41,6 % of all interested parties)
Mileage (35,8 % of all interested parties) Offer
price (29 % of all interested parties) Vehicle
type (25,9 % of all interested parties) Vehicle
location (23,9 % of all interested parties) Transmission
type (17,7 % of all interested parties) Vehicle
performance (17 % of all interested parties)
Colour (5 % of all interested parties)
In order to improve the lead quality of a car portal, it is advisable to divide the search into "rough" and "fine" searches, as is the case on the portal mobile.de and Co. But the criteria themselves would have to be selected differently according to the results of the latest studies, assigned to the different search masks and ranked.
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