Sales Metrics look at how well (or badly) the business is identifying potential customers, engaging them or capturing their attention, communicating to them about its products or services and marketing offers, and then convincing them to buy its products or services. This process of finding and converting new customers is referred to as the Sales Funnel, although the exact process will vary dependent on the business or industry, the product or service being sold, and the type of customer being sold to.
Traditional B2B Selling – traditional sales metrics
The more traditional types of business, especially those selling to other businesses (i.e. B2B or enterprise selling), especially when selling large investment products or high-value services, will usually employ a sales team who make several on-site visits, with a long lead time (Sales Pipeline) of familiarisation, communication and negotiation before converting the prospect to a firm sale. The reliance on a full-time sales team is an expensive sales model so tends to only be used where the product or service being sold is a high-ticket item, thus generating sufficient marginal profit to justifying the selling expense (e.g. a software installation of c. £150k for a one-off sale or £60k pa over a number of years).
Big-ticket B2B Sales Metrics (or Sales Funnel Metrics) can be split out as follows:
1. Number of new leads identified (Lead = they are generally in the market for something like what you offer, they want to buy or would like to buy at some unspecified time in future, but do not have a plan to buy or a budget to buy now, or a plan/budget to buy specifically what you are selling at the price you are selling it)
2. Number of qualified leads (Qualified Lead = looking to buy, in sufficient quantity to make it worthwhile/profitable trying to sell to them, AND able to buy i.e. can afford the product at your price level)
3. Number of decision-makers directly accessed/meetings held (Decision-maker = has both the budget and the authority to approve the purchase or sign the purchase order)
4. Number of expressions of interest received (we are going to buy this in the next 12 months and we might buy it from you)
5. Number of deals being negotiated
6. Number of soft-circle sales agreed (we will buy x items of product from you at y £)
7. Number of fully closed-out sales, with signed legal contract
8. Value of revenue booked
Modern Online B2C Selling – dynamic sales metrics
Modern internet-based businesses have an entirely different sales funnel and selling process, thus requiring a different set of sales metrics. They are generally high-volume, low-value business models, generating the required profit through selling at quantity. The variable costs of selling – particularly online – tend to be low relative to the company’s overall fixed costs of operation. They will be heavily reliant on the automation of as many elements of the marketing and selling process as possible, and ideally, automating all elements of both the sales funnel and as much of the distribution chain as possible. A clever use of persuasive and highly personalised sales copy will engage the customer and remove any sense of impersonal automation from the customer’s viewpoint.
Such businesses will rigorously and objectively monitor their selling metrics, with empirical testing and review being a key factor in their success. The industry best practice metrics in use by such companies are the dynamic sales metrics provided by internet-based selling (Clickstream Data). That is, those metrics which vary greatly in a short timeframe (< 1 month) and which are readily impacted by changes the business can make immediately or almost immediately.
Examples of Clickstream Data are: patterns of clicks and cursor movements, page views and page journeys, etc. Using such data, and the insights gained its analysis, allows an advanced internet-based company to customise the individual user’s website experience, thus optimising possible sales, while at the same time providing the base-level data related to products, inventory and orders. The basic data infrastructure will generally be provided through dynamic/real-time integrated links to a variety of different databases/data sources across the business. Individual customer customisation will come from the customer’s historical and current clickstream data. This will be further enhanced by historical order data from the individual customer themselves, and the order history of similar customers.
Examples of customisation of the individual customer’s user experience are:
- Individualised search results (based on: search term for e.g. product name/description/subject/category; ranked for relevancy using: previous order habits; similar customers’ order habits; other predictive algorithms for sales popularity)
- Recommendations (based on: saved wish list items; previously searched items; previous order habits; similar customers’ order habits; other predictive algorithms for sales popularity)
Online B2C Dynamic Sales Metrics examples:
1. Best-seller sales volumes/values and rankings (sales ranked within specific sub-categories or in high-level sales categories, etc.)
2. Co-occurring sales volumes/values (sales orders for multiple products placed by one customer in one order, including analysis of what is driving co-occurring sales to allow sales optimisation)
3. Co-occurring product views (views/clicks/browses by any one customer during current visit that results in the sale of at least one book to that customer, i.e. what other products were viewed together with the product purchased)
4. Up-selling and cross-selling metrics (how much and how often customers were persuaded to buy more than just one item originally intended to be purchased, including analysis of what is driving up-/cross-selling to allow sales optimisation)