September 19, 2018
A Checklist for Improving Buyer and Seller Engagement
Eliminating the friction associated with transactions is a core characteristic of successful marketplaces, because it makes it easier for sellers to earn extra money, while also making transactions possible that normally wouldn’t occur outside the marketplace.
Given the complexity of purchasing new and used automobiles, automotive portal operators face a unique set of challenges that marketplace operators in other verticals don’t face. Automotive manufacturers and dealers used to own the transaction, but with the rise of digital marketplaces, consumers/buyers are giving preference to platforms that deliver exceptional experiences.
With that in mind, let’s take a closer look at how automotive portal operators can reduce friction and enhance the customer experience.
The average auto buyer is bombarded with messages on a daily basis. Every buyer is unique and they want to be treated as the unique individuals that they are. In the past, it was enough for portal operators to send messages along the lines of “Hey there, [First Name], we have a few deals on [Car Model] today.” Those messages got the job done, but it really was more of a spray and pray approach to communications.
Today, it’s no longer enough to simply send out messages en-masse and see what sticks. Automotive portal operators need to leverage extreme personalization to stay ahead of the pack. This means communicating with buyers and sellers on a 1:1 basis. For example some buyers/sellers would prefer receiving notifications first thing in the morning while others are more receptive to content later in the day.
Extreme personalization is more than an improved way to deliver marketing messages to your buyers and sellers. It’s also an effective technique to reduce breakage and stalled transactions. With intelligent messaging, automotive portal operators can gently nudge buyers/sellers along the sales cycle depending on objectives.
One of the biggest hurdles to getting consumers and dealers to purchase automobiles through an automotive portal is a lack of context in pricing. In the past it was enough for buyers to reference Kelley Blue Book, but given the vast selection of vehicles on the web, having to constantly consult another information source adds an unnecessary layer of friction.
Kelley Blue Book only shows a rating. It doesn’t explain the “why” behind the value. Automotive portal operators need to justify their pricing by calling out vehicle attributes that are affecting price, while also considering supply and demand. This enables dealers to be more transparent, show value beyond price, and close deals more efficiently.
If you choose to deploy a price badge within your marketplace, you’ll want to ensure that the ratings are dynamic, and that they are tailored to each vehicle type, as opposed to taking a one-size-fits-all approach across the board. For example, price indicators for luxury vehicles shouldn’t use the same criteria as those for compact cars.
Artificial intelligence-powered price recommendation engines remove friction in the car buying process by using machine learning to factor in the demand for vehicles within a geographic region.
Given the fact that purchasing a vehicle often involves speaking with multiple individuals, and spending weeks on research, it’s easy for dealers/consumers to drag things along without making progress towards a purchase. This is where predictive selling indicators come into play.
They’re common in digital marketplaces as they provide insights into how quickly an item will move on the market. Travel portals commonly use them to indicate when airfare or hotel prices are likely to rise. Retailers use them to highlight when an item receives a surge in demand or is likely to sell out. In both of these cases, the buyer is nudged closer to a purchase.
Despite the high value of automobiles, buyers still have a fear of missing out on great deals. Predictive selling indicators enable portal operators to indicate which cars are in-demand based on leveraging machine learning to consider car make and model, geographic demand, time on lot, along with pricing and consumer indicators.
For example, an automotive portal operator can drive urgency by indicating when a specific model of a vehicle is likely to sell within 7 days of being listed.
When it comes to purchasing new and used vehicles, modern car dealers and consumers are turning to portals as a way to streamline the purchasing experience. Given there’s no shortage of platforms where buyers and sellers can transact, automotive portal operators need to do whatever they can to stay ahead of the competition.
This requires a different way of thinking. Rather than focusing on unloading inventory, portal operators need to put themselves in the shoes of their buyers and figure out ways to add value. By becoming a trusted partner, rather than a salesperson, the portal operator can remove the tension associated with purchases and therefore drive sales.
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