Sales Enablement with Ecommerce (and data)
The Evolving Role of Sales in the Digital Age
In 2017, 68% of B2B buyers preferred doing business online versus with a salesperson, and when they engaged with sales, buyers wanted a consultative experience, according to Andy Hoar’s well known, Death of a Salesman: Two Years Later. The fear from sales people that they will be displaced still exists in 2021, but the role of sales has shifted dramatically from an order capturer to that of an advisor. To reference Hoar once more, Nike doesn’t have its Footlocker account sales representatives writing down what products Footlocker is considering putting in its next plan-o-gram layout. Nike’s reps are working hand-in-hand with Footlocker to maximize floor plans to ensure the highest margin per square foot.
B2B buyers have demanded the transformation of classic sales relationships to the new sales representative and buyer relationship presented in the The Challenger Sale by Matthew Dixon and Brent Adamson. The best selling book highlights Grainger as a case study in digital transformation and sales enablement. Grainger sales representatives are no longer order takers, but consultants.
According to Caroline Ernst, Ecommerce VP at Affiliated Distributors, in a DigitalCommerce360 article, digital transformation is at the forefront of all C-level priorities due to COVID-19, and challenger reps are taking full advantage of the situation by helping buyers navigate the digital environment and leveraging ecommerce sites for product education and self-service. Ernst goes on to state,
“another challenge was that communication channels shifted to digital, and customer support and sales teams needed to meet their customers’ needs without having that in-person touchpoint.”
Transforming the traditional sales department hierarchy is the first step in enabling the future of sales. This means providing access for sales leadership, customer service, inside and outside sales reps, and even third party sales rep organizations, to the digital sales channel(s) - the ecommerce platform and related data. The following article will explore the complementary pairing of sales and ecommerce, the types of ecommerce data that can feed sales enablement activities, the collection and presentation of data, and tips on adding value to the customer with ecommerce data and in-turn enabling more sales.
Why Sales Enablement + Ecommerce
According to Distribution Strategy Group’s 2021 State of eCommerce Distribution: Part 2 report, “[sales] people are still the No. 1 most effective way to drive demand to an ecommerce channel for most distributors. Field sales reps, inside sales reps and customer service reps are highly effective for most distributors in driving demand to ecommerce.” The report states that field sales reps are the leading source for adoption above any other channel.
If sales representatives are the most effective way to drive demand and adoption to an ecommerce platform, how can sales through the channel be optimized? The three primary ingredients to sales enablement success are training, content and tools. Additionally 20% of distributors reported the lack of sales rep support being an issue, and many distributors may not even understand the magnitude of this issue as B2B ecommerce is still relatively immature.
Ecommerce provides the content through product catalogs and the tools to empower sales enablement that allows well trained sales professionals to challenge and educate buyers. Diving slightly deeper, those product catalogs can be personalized to accounts based upon data from similar customers to maximize opportunities in the product mix and even allow for staged industry specific product catalogs when negotiating deals. This results in increased sales because of optimized product mix, speed to serve catalogs, and confidence that customers will receive valuable insights from sales consultants. All of this is powered by the data available in the ecommerce platform.
Sounds simple, yet the pandemic showed the gaps in B2B ecommerce maturity. Sales reps were quickly moved from production floors to their basement offices in a new work-from-home world. Unfortunately, while ecommerce sales grew at unprecedented rates, many sales people were stuck logging into a VPN and searching for sales data through a slow connection to an ERP or asking an IT employee to write repetitive reports. This is the state of sales enablement, 2002 style, in a 2020+ pandemic.
Types of Ecommerce Data for Sales Enablement
Data is the tool to drive powerful conversations with customers. Sales people need to move from order takers to order makers and organizations need to train them to use data and provide opportunities like an ecommerce platform executes. This means understanding a myriad of key performance indicators (KPIs) and using this data to increase margin, assortment and revenue. Following is a list of ecommerce KPIs that can be utilized in sales enablement to offer value to customers when analyzed and curated for sales reps.
NOTE: Conclusions from the analysis of ecommerce KPIs can be drawn in a multitude of ways; however trends tend to appear clearer when KPIs are organized on a similar account type or customer groupings (segments).
Order Data
Average order size/value (AOV): the average total of every order placed over a defined period of time. Why? AOV can be viewed across an entire portfolio of accounts if grouped by company type or industry to identify purchasing trends across segments.
Average margin: the average of profit margin percentage of every order placed over a defined period of time. Why? Average margin can be utilized to identify low or high margin products that are gaining traction.
Gross profit: is calculated by subtracting the cost of goods sold (COGS) from revenue (sales). Why? Gross profit can prioritize specific types of deals sales reps should focus on, high profit and minimal effort vs. low profit and significant effort, however this does not mean sales reps should prioritize deals that can be handled frictionlessly through the ecommerce platform.
Number of orders: the total number of deals closed by a sales rep’s account portfolio over a defined period of time. Why? Value can be added if the account's order frequency is increasing by restructuring supply chain offerings.
Conversion rate: the percentage of website sessions (by account or segment group) that places an order over a defined period of time. Why? Analyzing conversion rate by account can identify the level of adoption of the ecommerce platform and then allow sales reps to remind customers of the self-service capabilities of the platform when appropriate.
Quote Data
Average quote size/value: the average total of every quote submitted over a defined period of time. Why? Comparing AOV to average quote value allows sales reps to see what products were eliminated from orders that have been placed. Opportunity may exist in those un-purchased products.
Average quote margin: the average profit margin of every quote submitted over a defined period of time. Why? The average profit margin of quotes should be compared to orders submitted as to identify what un-purchased product should be prioritized by sales reps to push in future engagements.
Number of quotes: the total number of quotes submitted by a sales rep’s account portfolio over a defined period of time. Why? The number quotes that are submitted that do not translate into orders could be a sign of customers cross shopping and could signal the need for account engagement.
Quote approval status: the step in which a quote is during the approval process for conversion to an order. Why? Analyzing in which step quotes sit can identify blockers in the deal closure in multi-approval process deals.
Quote to order rate: the percentage of quotes that transition into orders (by account or segment group) over a defined period of time. Why? Accounts with a low quote to order rate may need to be re-engaged or further analyzed to determine the block in conversion (this may or may not be a sale’s related challenge).
Cart Data
Abandonment rate: the percentage of carts that are created that do not transition into orders over a defined period of time. Why? Similar to the number of quotes created, those accounts that are creating a significant amount of carts and abandoning them could mean being cross shopped against the competition and could signal the need for re-engagement.
Products added to cart: the products added to the cart (simple). Why? This KPI has a multitude of reasons to be evaluated in enabling sales as products added to a cart are the first step in putting together a shopping list, and even a quote or order. If those products are in-turn ordered, analysis can be completed as to which specific options were selected and which were not. Sales reps can also look to see if there are product benefits or complementing products that are or are not being ordered that could be suggested to complete a customer’s kit.
Cart totals: the total cost of products in a user’s cart. Why? If cart totals are significantly higher than order totals it could mean that specific accounts are adhering to strict budget restrictions and that opens an opportunity for sales reps to propose pricing or contract negotiations with a goal to increase the total number of order line items for the account (while achieving the same or higher profitability).
Promotions/discounts applied total: the total of discounts applied prior to order submission. Why? While this can also be analyzing post order submission, analyzing it prior to order submission provides the opportunity for sales reps to identify additional savings to be had by customers.
Product Data (in correlation to product utilization: viewed, quoted, ordered and returned)
Categories: the most popular product categories based upon product utilization. Why? Analyzing product categories can allow for the suggestion of like products to those being ordered but may offer additional benefits not known to customers.
Attributes: common products based upon product utilization. Why? Identifying commonality between products via attributes can uncover similar products at lower costs, with more benefits, and/or higher margin products to be suggested to customers.
Catalog inclusion: product mix across the entire sales rep account portfolio based upon product utilization. Why? When account portfolios are created and based upon similar accounts and even when based upon geographical territories there will be similarities and trends of the products being utilized in catalogs. Analyzing product inclusion will identify gaps in specific account catalogs that can be filled by products popular across the account portfolio.
Product affinity: the frequency of products being purchased together. Why? Products being purchased together can allow for the creation of kits and bundles that can further simplify customers' ordering process and ensure product consumption going forward (buyers are creatures of habit, enable their habits).
Product relationship: products that are being viewed consecutively. Why? If products are viewed in consecutive order there is a good possibility that consideration is being made about which product to order.
Product lots: a production metric often tied to products that have usage timeframes. Why? Identifying when previously ordered products are going to expire provides a sales rep the opportunity to re-engage and inform the customer that their current product may not be up to specification if being utilized in production.
Shipment Data
Order status: the current step in which an order is in the fulfillment process. Why? Being able to inform customers the current order status seems relatively rudimentary however many organizations are not able to provide sales rep’s transparency to whether customer’s orders are backordered, picked, packed, shipped, or delivered.
Orders shipped: the number of orders shipped over a defined period of time. Why? Examining the number of orders that have been shipped allows a sales rep to predict when an order will be shipped for a newly placed order as well as the effectiveness of the supply chain for the individual customer.
Shipment tracking: where any order is in transit to the customer’s shipping address, typically provided by carriers and/or logistics companies. Why? Analyzing the shipment tracking of an account’s order history was previously a permission reserved for supply chain management, however, if sales reps are privy to such information explanations and solutions to, “where is my order” questions become less taxing on the sales rep.
Split shipments: the total number of orders that were split in fulfillment shipments over a defined period of time. Why? If orders are being routinely split because of specific products, this could be an opportunity for supply chain optimization or an order placement behavior modification. Regardless the sales rep can understand the customers interactions with the business at a deeper level to better provide value.
Frequency of shipment delays: the number of orders that are delayed in comparison to expected shipment dates over a defined period of time. Why? If supply chains are internally managed sales reps can set appropriate expectations with customers about the potential for delays and customers can better prepare for the impacts such delays might cause.
Frequency of shipment types utilized: the consistency in which a specific shipment type is selected by a customer for an order. Why? As a negotiation leveler sales reps can utilize shipment offerings as a pricing mechanism and/or provide better inventory planning recommendations as to avoid high cost shipping option usage.
Return Data
Return request frequency: the number of account returns requested over a defined period of time. Why? If your organization allows returns, analyzing the frequency of an account's return requests can provide insights as to the level of satisfaction with products or services being provided.
Returns authorized: the number of account returns authorized over a defined period of time. Why? Sales reps should understand the returns that have been authorized in the past for an account as to avoid a similar situation in the future.
Returns denied: the number of account returns denied over a defined period of time. Why? Analyzing return requests that have been denied will prepare sales reps to have alternative products that can provide the benefits that customers are seeking.
Returns completed: the number of account returns completed over a defined period of time. Why? Successful returns can be utilized as leverage by sales reps in the negotiation process.
Account/User Data
Lifetime value: current value of goods a customer has ordered. Why? Analyzing the lifetime value of a customer account allows sales reps to prioritize efforts and understand the life expectancy of an account, including likely to continue ordering.
On-hand inventory: current amount of products an account has within their control. Why? Ecommerce provides the detailed information on products customers have ordered over the lifetime of the relationship so on-hand inventory data will provide sales reps the opportunity to revisit previously purchased products.
Collection and Presentation of Ecommerce Data
Organizations that have invested in ecommerce still struggle with the accessibility of data from an ecommerce platform. Beyond silos, reporting issues and a slow ERP sitting in the middle, many companies turn to CRM solutions which focus on reporting sales activity, rather than customer buying activity. While some organizations intended to marry data from multiple systems into CRM dashboards, few have been successful without years of significant financial investment. Ecommerce data already resides in an ecommerce platform, which can also pull offline data and historical data from an ERP. This data is just waiting to be manipulated to show value for sales reps and their account portfolios.
Ecommerce, Adding Value to the ‘Sales and Buyer’ Relationship
To arm sales reps with ecommerce data in an easily accessible and organized structure, and assist in providing value to an entire account portfolio, Znode recently released the first evolution of the Sales Enablement Console. This console combined with the Commerce Connector framework for exchanging ERP data and Znode’s native Microsoft Power BI connector, provides Znode customers with the tools and data to support sales enablement and the transformation from an order taker organization to an order maker enterprise.