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“This Sells with that” for Aftermarket Parts
The SKUs (stock keeping units) in an aftermarket business is nothing but the various components of an automobile, tractor or backhoe. Every new model that comes into the market sees an addition of 2,500-3,000 parts to the existing master list, while the addition of every variant adds another 500-1,500 parts. The last forty years has seen a phenomenal growth in the number of aftermarket parts. This phenomenal growth has been fuelled by the liberalization of global players resulting in thousands of models of cars, tractors and other machines.
Frequent launch of new models has reduced product life cycle and has negative implication on the aftermarket supply chain. The implication of shorter life cycle of automobiles on the aftermarket business is faster transition of parts from runners to repeaters and soon fading into obsolescence. The revenue from parts of a new model are typically low in the first two years after launch, increasing in the third and fourth years. The sales only stabilize if the model continues in the market. Unlike other businesses where a product is discontinued if it does not yield revenue, in an aftermarket parts business the part needs to be supplied even if the model has failed. This tremendous volatility impacts the number of parts the aftermarket business has to support.
For example, if an OEM introduces a new model and two variants each year – this results in about 3,000 parts. In six years time the parts proliferation in the aftermarket business of this OEM will be least 30,000 parts. This explains the relevance of having a SKU management for the aftermarket business in order to track the movement of parts till it reaches obsolescence.
Levering “this sells with that” Intelligence from Invoices
The challenges due to inventory and assortment planning for the aftermarket parts are significant. Traditional forecasting methods that treat each part as an independent entity are outdated. For aftermarket parts, the performance of traditional forecasting methods is dismal, and hence not all the parts can be forecasted. In fact, only five percent of the master list can be forecasted with an accuracy of 75 percent on a monthly basis. This results in bloated inventory, incorrect parts assortment and lost sales.
OEMs, distributors and retailer have realized the importance and complexities of the spares business and have initiated measures for assortment planning and SKU management. This requires sustainable methods as the market grows and competition gets fiercer. Every OEM has mentioned how the downturn has reflected in increased sales for the aftermarket/service parts. A part of the business that was typically ‘a nice to have’ has become a focus for improved customer service and profit.
"This Sells With That" For Aftermarket Parts
The aftermarket business deals with SKUs in tens of thousands. Unlike soft goods, in this business customers buy parts for projects and jobs. The invoices reflect that, and are comprised of parts bought by maintenance and repair shops to get a job done. Hence, the affinities in the sales transactions reveal what parts that are bought together for repairs/jobs.
The sales transaction data for the aftermarket businesses is very rich with parts affinities and trends. That’s because the data reflects the buying patterns of repair shops and mechanics. This represents a significant opportunity to leverage the transaction patterns for assortment planning, inventory management and of course, ‘suggestive selling’.
Emcien offers analytics that reveals patterns in sales transactions, producing a complete data map of the item affinities for ALL parts. This intelligence can be input into traditional warehouse planning and retail assortment planning systems. The affinities data can be used to make traditional systems smarter as the sales patterns change, parts change and market shifts.
The current sales patterns and item affinities in planning systems are input manually using manufacturer recommendations and gut feel. These recommendations get stale very quickly and are rarely based on actual sales invoices. The value of analytics driven affinities is that the relationships are always up-to-date, backed by actual sales transactions. Emcien’s analytics produces affinities data for all parts in the supply chain eliminating the need for ‘hard coded’ rules that quickly become obsolete and are a nightmare to maintain. This enables aligning parts inventory with with sales/model changes/parts utilization based on actual invoices. The affinities data can also be use for suggestive selling to increase customer service and order size.
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Tips for Suggestive Selling to Increase Order Size
An online presence is considered a necessity for business today and the Internet is perceived as a significant revenue generator. However, most e-commerce websites, with the exception of Amazon and Proflowers, have not reported great sales. The disparity between the number of clicks received and the actual number of customers is stark, proving incredibly low conversion rates. Therefore, along with determining the revenue targets and projecting growth plans, you have to master strategies to increase order size.
Suggestive Selling: The Best Way to Increase Order Size
Developing online trust and enhancing a visitor’s shopping experience might gear visitors toward a particular website. However, attracting traffic and converting them into customers is not sufficient. You have to focus on increasing the order size to drastically improve sales. The most effective way to achieve results is suggestive selling.
Increase Order Size By Suggesting Highly Relevant Items
Although suggestive selling or up sell/cross sell is greatly dependent on the products being sold, the following are some tips that can improve e-commerce sales:
Positioning of up sells and cross sells: Place up sell and cross sell offers in as many product pages as possible. While big merchants will be at an advantage in this regard (since they have a larger inventory), smaller merchants have to exploit every single opportunity to increase order size. However, placing suggestions at strategic points is crucial. Remember that you want to:
• Firstly, educate the visitor about every related item available
• Secondly, inform them about the depth of your collection
Trust impulse sales at the last minute: The E-Tailing Group survey states that 38% of all e-commerce websites place up sells in the check-out page, which the customer visits after putting all items in the shopping cart. Placing seductive offers in this page works wonders. However, there are a few rules to be remembered:
• Offer a variety of price points
• Low-dollar products make for more probable impulse purchases
• Ensure that the most relevant items are offered, for example, a shirt or belt with pants
Include up sell and cross sell offers in post-order e-mails: Inclusion of additional products in all customer e-mails can boost sales significantly. Many e-commerce websites do not follow this strategy, believing that goading customers into purchasing products reduces purchase scope. However, this tactic cannot be termed as ‘goading’ since the recipient is a customer who has previously purchased from your website. Therefore, including cross sells in support or product enquiry e-mail replies and post-order e-mails is a practical solution.
Not more than three products supplementing each purchase item: The old saying ‘less is more’ proves true in this regard. Overwhelming customers with too many offers is not a good idea. To catch a shopper’s attention, there should be an average of three cross sell suggestions.
Category-bundle techniques: Package deals are one of the newest trends in e-commerce. Follow the brick-and-mortar store technique and position complementary products in such a way that consumers feel that buying the entire ensemble will serve their needs. This can be done with all items – plumbing products, electrical products, auto parts, office products, furniture, sports gears and so on.
In addition to this, you can consider hosting automated expert recommendations based on customer buying patterns and trends. This has great potential when it comes to raising sales. Automated suggestive selling ensures that the suggestions are always up to date! This is key as retailers today offer hundreds of thousands of items that are constantly changing. Manual methods for updating complementary products are just not feasible.
Increasing Order Size With Basket Analysis
I came in to buy milk and I am walking out with 10 things in my basket. The man behind me had only one item in his basket. “How do you do that?” I asked. “It depends on what you come in to buy,” he responded.
There are a few “seed items” in the store that drive additional sales because of key concept ‘this is often bought with that’. These items are often found together in customer baskets and orders. Smart retailers will put these items as far away as possible, so that you have to walk through more aisles to get from one item to the other, in hope that you will buy more along the way. Bread and milk is a good example of that. The reverse is also true. For items that are often bought together, if the store does not carry both, they will lose the customer.
Every retailer knows that it is very profitable when a customer comes in to buy one item, but ends up with many more in his basket. Understanding the product relationships in the market basket is key to driving up the order size or basket size.
Understanding the Customer basket make-up
A retailer typically carries thousands of items. A small convenience store may carry 1,500 items. A grocery store typically carries 15,000. And the super stores like Wal-Mart and Targets carry well over 25,000 SKUs in each store.
Insight Into Customer Baskets and Product Relationships Based on Buying Behavior
The SKU management is a tremendous challenge because the buying pattern is truly a long tail. Retailers know their top sellers; these are easy to identify, but the frequency of buying falls of very sharply. The chart shows an example of one retail store operation over a 3-month period. The store carries 25,000 SKUs, has 100,000 transactions per month. The analysis covers a 3-month period, and shows the distribution and popularity of SKUs based on the frequency of purchase.
Here are some quick stats for insight into the baskets and buying behavior – The most popular SKU has a frequency of 3,435. That means is has been bought in 3,435 baskets. The frequency of the 100th most popular item drops off to 225. That means it is only in 225 baskets over the 3-month period. There are 4,000 SKUs that are bought only once. But the really interesting fact is that 1,800 SKUs are bought together 98% of the times. None of these 1,800 SKUs are top sellers! But when they are purchased, they are very often paired with other items. This intelligence is key to increasing basket size and ensuring the store is carrying the right items. SKU rationalization analyses that view each SKU as an independent item, that is bought in isolation, will result in incorrect merchandising and lost sales.
There basket analysis also showed the low-frequency/high-correlation SKUs. Every retailer knows the challenge with these items. These items sell rarely, they sit on the shelf for along time, and when it is placed in a basket it will only sell if the paired item is available! These are problem SKUs because they are capital hogs and always show up in inventory issues.
Insight into the basket make-up and the product affinities based on buying behavior is key to merchandising and increasing order size. Merchandizing, up selling, cross selling and add-ons based on buying behavior results in increased sales and enhanced customer experience. On the other hand, suggestive selling based on tribal knowledge and ‘he said/she said anecdotes’ will result in poor results and loss of customer good will.
Adding one more item to 10% of the baskets can increase sales by 5%
Sales Impact Of Increasing order size
The basket size or order size analysis shows the revenue potential of increasing the order size. The chart shows a typical basket size analysis and the upside opportunity of increasing order size. The results from this case study showed that adding one more item to 10% of the baskets can increase sales by 5%.
Manufacturers, distributors and retailers offer thousands of products. There is a significant opportunity to increase sales across all channels with knowledge of product relationships (what items sell together), when and where. It is commonly agreed that B2B purchase behavior is “need based” while a large percentage of B2C sales is emotion based. Hence, in B2B commerce, the product relationships have to be highly accurate to be relevant.
Quick review of definitions:
Frequency – Number of orders that contain this item
Volume – Number of items sold.
The volume of an item may be high because one customer bought a lot. However, frequency is better measure of popularity and is not skewed by a one-time large volume sale. In fact, SKU analyses will often remove large volume buyers to reduce this bias.