How to Track Your High Ticket Leads

How to Track Your High Ticket Leads

Your CRM contains the information gathered by your sales team during an inbound or outbound call as well as email communications (hopefully). These information entries are made manually by your team and as such can be limited in details and difficult to decipher.

System entries in more advanced systems often starts before the sales call. This serves well to understand the purpose of the call, helps for lead nurturing to prepare the client for that call. Having a CRM organized that way helps by avoiding duplicated touchpoints and information that does not help to the sale and sales development.

High-ticket vs. low-ticket

Our agency understands that high ticket sales outbuilding construction companies are typically not as advanced as low ticket retail e-commerce companies in digital marketing. This is particularly apparent when it comes to collecting the client's browsing information across multiple devices, which is not always an easy task. This is however getting easier as your sales mostly comes increasingly from inbound calls dialed from a smartphone to your sales representatives call center.

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Lead generation for high-ticket sales

As a comparison, trade shows has often been the biggest source of qualified leads for many specialized outbuilding construction companies. At those events, leads are collected manually and retargeted later on. Your 1 or 2 representatives will write down as much information as they can on a prospective client and this of course will have it's limitations. In essence, the current technology allows us to do the same thing, but doesn't limit itself to trade shows, geographic location or volume.

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Metadata aggregation process

Here is an example of a spreadsheet used for metadata aggregation. We use a spreadsheet like this before setting up an API connection with a client’s company CRM. If for some reason the data connection is not working as it should, we will have this log to troubleshoot ands still collect data. The process is fairly unlimited, as we do not have to worry about the number of fields added for 1 client.

Many bulk operations can be performed for matching duplicates and combining everything in one place for the various members of your team. This is really a cost effective way of collecting lead data. We can then setup reports that focus only on the data your sales or marketing director needs to see quickly to make a decision. This is the first milestone to a successful digital marketing campaign.

Prioritize tracking mechanisms

Tracking needs to be setup first otherwise the data isn’t reliable and incomplete. Companies that fail at this are also missing out on opportunities to optimize and remove resources from campaigns that do not produce ROI. This will expand your understand of your top client’s persona (in traditional marketing) and allow you developed the optimized campaigns using new means based on your existing models.

We are not trying to reinvent the wheel just make it more efficient. This is all done seamlesly and does not affect your brand’s image in a negative way, as it is all achieve with your client’s explicit conscent.

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What is data aggregation?

Data aggregation is the process of gathering data and presenting it in a summarized format. The data may be gathered from multiple data sources with the intent of combining these data sources into a summary for data analysis. This is a crucial step, since the accuracy of insights from data analysis depends heavily on the amount and quality of data used.

It is important to gather high-quality accurate data and a large enough amount to create relevant results. Data aggregation is useful for everything from finance or business strategy decisions to product, pricing, operations, and marketing strategies.

What is an example of aggregate data?

Here is an example of aggregate data in business:

Companies often collect data on their online customers and website visitors. The aggregate data would include statistics on customer demographic and behavior metrics, such as average age or number of transactions.

This aggregated data can be used by the marketing team to personalize messaging, offers, and more in the user’s digital experience with the brand. It can also be used by the product team to learn which products are successful and which are not. And furthermore, the data can also be used by company executives and finance teams to help them choose how to allocate budget towards marketing or product development strategies.