By Swati Sahai
‘90% of customer value for B2B businesses is obtained after the initial sale.’ – Marketo
“Would you like fries with that?”— McDonald’s classic question is perhaps the best-known example of cross-selling.
Amazon has attributed upto 35% of its revenue to cross-sell, both through its “Frequently Bought Together” and “Customers Who Bought This Item Also Bought” features.
JetBlue has in the past made as much as an additional $140million in revenue through its upsell program called ‘Even More Space.’
Meanwhile, Lufthansa uses VR glasses to entice travelers into last-minute upgrades to ‘Premium Economy’ at the boarding gate and acknowledges that this successful upsell program has brought in significant ancillary revenue.
There are many such examples of B2C and B2B companies that are using upsell and cross-sell opportunities to generate profits. Yet marketing budgets continue to focus heavily on new customer acquisition at the expense of driving upsell/cross-sell and retention of existing customers.
In this post, I take a detailed look at:
- What is upsell and cross-sell? Are they the same?
- Why is upsell and cross-sell important?
- 5 steps to find better upsell and cross-sell opportunities using journey analytics
Upsell Or Cross-sell? Are They the Same?
Upsell and cross-sell are often confused and used interchangeably, but there is a meaningful difference between the two.
Upsell is when you encourage your customer to buy a higher priced alternative of the current consideration. Upselling encourages customers to purchase a more expensive model in the same product or service family, or to augment the original purchase with additional features such as warranties.
A familiar example is when retailers offer consumers to add a protection plan to their purchase, as shown below.
Cross-sell is when you recommend a product that complements your customer’s existing purchase, but is from a different category. In this case, the retailer in the previous example offers a complementary product to the one already chosen.
Cross-selling identifies products and services that satisfy additional, complementary needs that are unfulfilled by the original purchase. A common example in retail banking is when your bank offers you a credit card after you open a new savings account.
Cross-selling and upselling are closely related because they both focus on providing additional value to customers, rather than limiting them to products they have already considered or purchased. The key to success in both is to understand what your customers value most and then respond with products and services that truly meet those needs at the right time and through the optimal channel.
Why are Upselling and Cross-Selling Important?
1. Generates Additional Revenue More Efficiently Than Selling to New Customers
Lead generation is expensive. It is far easier and more profitable to upsell or cross-sell an existing customer than to make a new sale to a brand new customer.
A SaaS benchmarking survey looked at the customer acquisition costs (CAC) needed to acquire $1 annual contract value (ACV) for new customers compared to upsell to existing customers. The results showed that the median CAC for $1 of new ACV was $1.18. This means that it would take a company more than a year to earn back the cost of acquiring new customers.
The median CAC per $1 of upsells was only $0.28, about 24% of the cost to acquire each new customer dollar. The payback period for upsell revenue is only about a quarter, far less than that of new customers.
2. Builds Stronger Customer Relationships
Upselling and cross-selling is not just a sales and marketing tactic to make more money for a company. When done right, it helps a customer derive more value out of their purchases, do their jobs better and make their lives easier. It generates more opportunities to provide good customer experiences and build deeper, stronger customer relationships.
3. Leads to increased Customer Lifetime Value (CLV)
Upselling and cross-selling are great ways to increase your customers’ profitability over time and keep them coming back for more.
Geico Turns Customer Service Into Cross-Sell Opportunity
Here’s a great example of upsell done through a support call leading to a higher CLV. Chris Yeh, an investor and entrepreneur, called Geico for roadside assistance and ended up narrating the whole incident on his blog:
“This post isn’t about the $2,000+ I’m going to have to spend on a new transmission. Rather, it’s about how GEICO turned a pure cost center–providing roadside assistance to its customers–into $2,000 in revenue. After providing GEICO with my location and arranging to wait for the tow truck, the GEICO dispatcher told me, ‘From looking at your account, it looks like you’re now eligible for a big discount on our comprehensive coverage. Since you’re going to be waiting for the tow truck anyways, would you like to hear more?’
15 minutes later, I had agreed to add $1 million in additional coverage for my car and home, at a cost of right around $100 per year.
I’ve been a GEICO customer for 16 years already, so it’s not much of a stretch to speculate that I might be a customer for another 20 years. That means that GEICO turned a costly customer service call into an incremental $2,000 in lifetime revenue.”
5 Steps to Find Better Upsell and Cross-sell Opportunities Using Journey Analytics
1. Take a Journey-Based Approach
The first and most important step to find new upsell and cross-sell opportunities is to take a journey-based approach. It is necessary to have an omnichannel view of the customer throughout the journey, over time and across multiple touchpoints. Only by having this full view can you get the complete picture of the customer’s likes, interests, behavior and sentiment—all of which are needed to present the best offer in any given moment.
Businesses previously did not have visibility into real, end-to-end customer journeys, so they were forced to rely only on the last one or two customer interactions to make decisions on cross-sell and upsell offers.
Customer journey analytics is a breakthrough technology that provides the power to look across millions of complete journeys connecting multiple touchpoints over different channels and time periods. This has motivated marketers to reassess cross-selling opportunities.
For example, Bain & Company recently analyzed the telecommunication industry and found that nearly 60% of customers split their mobile, internet, TV and landline services across multiple providers. Convincing just 10% of those customers to switch even one service away from a competitor, could mean an incremental revenue of $480 million for the telco.
This is a huge opportunity. To execute on it, customer journey analytics for telecom companies executes campaigns based on past behaviors, events, sentiment and interactions across touchpoints.
2. Build an Omnichannel Customer View
A typical shopper today may first come across a product through a social network ad, check it out on an ecommerce site and purchase it in a physical store. But are you equipped to see this customer as a single person and not three different shoppers? A large majority of companies still see each device and each interaction as a separate customer, breaking the customer journey into disparate fragments.
If marketers want to make cross-sell and upsell offers that will have a high win-rate, even as customers hop across channels and devices, they must have a complete, single customer view across all their touchpoints.
A customer journey analytics platform enables you to get a single, unified view of the customer by quickly integrating data across a variety of systems and channels such as point-of-sale systems, email marketing platforms, marketing automation systems, data warehouses, websites, surveys, call centers, clickstream, chat, etc.
In addition to simply integrating data across touchpoints and internal systems, customer journey analytics tools use identity matching to determine which events in each system are actually being performed by the same individual. For B2B marketers, high-quality, real-time customer data is important for making personalized recommendations in the moment and providing an exceptional customer experience.
B2B cross-sell and upsell can be improved by incorporating data like:
- Which features are being used
- Whether their subscription is up for renewal
- How many new users have they added
- When there is a role change, such as a new product champion
Having this data at every step along the customer journey will increase the chances of a cross-sell/upsell campaign manifold.
3. Create Dynamic Customer Segments Based on Behavior
As my colleague Gary DeAsi wrote in a recent post, behavioral segmentation is a powerful approach to drive growth and expansion through cross-sell and upsell. Companies like Amazon employ machine learning algorithms that use customer behavior data—such as a user’s purchase history, items in their shopping cart, and items they’ve previously rated and liked—to make product recommendations.
Dynamic customer profiles
Internal and external data that spans several years can be combined to build dynamic customer profiles. Knowing how the customer’s product usage has changed over time, how she has migrated among different products and which factors caused change in behavior are all valuable in designing effective share-of-wallet strategies.
Customer behavior data can also be used to determine when not to target some customers for an offer. For instance, if a customer has had a recent negative experience with your company or are not getting enough value from products they’ve already purchased, it is probably not a good idea to make them a fresh offer.
A Harvard Business Review article identifies four profiles of customers you should avoid cross-selling or upselling to as they may in fact be unprofitable for the business:
- Service Demanders. This customer segment often overuses customer service channels and tends to call support for every issue that they encounter, often ignoring service announcements. When service demanders purchase more products, your support costs rise disproportionally.
- Revenue Reversers. Revenue reversers give the appearance of generating revenue, but then take it back as they are more likely to return items, default on payments or terminate contracts early. The more they buy, the more they display such behavior, costing your company time and money.
- Promotion Maximizers. This segment gravitates towards steep discounts, making them unprofitable for the company overall.
- Spending Limiters. Spending limiters have a small, fixed budget that they will not exceed with a company. If they buy additional products, they will not increase their total spending with your company. Therefore the money you spent in cross-selling to them was not recovered as they did not generate any additional revenue.
In order to identify these unprofitable customer segments, you have to mine behavior data and track each customer’s end-to-end journey, so you can make dynamic cross-sell and upsell decisions that are efficient and profitable in the long run.
4. Use Predictive Analytics to Provide New Product Recommendations
Customer journey data can be used to predict each customer’s likelihood of responding to a cross-sell or upsell offer. Input data can include the products and/or services that are commonly purchased and used in conjunction with one another. This data can be further analyzed to identify which customers bought, as well as the dates when the purchases were made.
This knowledge is valuable for the product marketing team to create product and pricing bundles. These product recommendations are also valuable to provide to customer support teams, so they can make real-time cross-sell or upsell suggestions based on each customer’s specific situation.
Hyatt Hotels Uses Predictive Analytics to Boost Revenue
Hyatt Hotels has aligned its operations across 500 hotels globally to use predictive analytics for cross-selling and upselling.
Hyatt used guest history and preferences from their membership program to identify guests with similar profiles and create customized offers for each based on a unique combination of amenities, room upgrade, or activity packages. The program worked by prompting front desk agents with relevant and timely messages such as, “Based on what we know, this person will want a room with an ocean view” or “This person will likely be looking for a spa package.”
Using predictive analytics for cross-selling and upselling, Hyatt was able to increase the average incremental room revenue post reservation by 60%, compared to similar programs in the past that did not use sophisticated analytics.
The hotel industry, in general, is rich with raw data, which when stitched together throughout the customer journey, allows marketers to move past basic audience attributes and discover more specific and relevant attributes for better engagement and personalized service offerings.
The most common barrier to getting and implementing real-time insights is that the data lives in silos in disparate systems such as property management system (PMS), point-of-sale (POS), central reservation system (CRS), call center, spa, food and beverage department etc. In most cases, this data does not get consolidated with the rest of the hotel’s online data from web analytics, guest satisfaction surveys and social media.
Customer journey analytics platforms can solve this problem by integrating data from different sources into one central platform that sits as an intelligence layer with existing technology stack. In this way, customer journey analytics generates insights for marketers and customer experience teams.
5. Efficiently Execute and Measure Cross-sell and Upsell Campaigns In Real Time
Customers today expect personalized, relevant information and offers driven by their preferences, recent interactions and latest product and support experiences. They are ready to abandon their journeys with a single poor experience. Companies cannot afford to falter or even provide a sub-par interaction at any step along the entire customer journey.
To improve the performance of cross-sell and upsell campaigns, marketers need to be able to make the most relevant offer to the most potentially profitable person, at the most opportune time, via the most appropriate channel.
Customer journey analytics enables marketing teams to do just that. By embedding triggers at any event along the journey, you can activate engagement (such as an email send) to your target customer group within a specific event—customers who converted, those who moved forward or even those who dropped out at a particular point in their journey.
Advanced customer journey analytics platforms integrate with commonly used marketing tools, so you can engage with your customers using your existing marketing technology stack. The result is a new level of performance for marketing and CX campaigns through significantly better precision, targeting and timing.
Finally, to gauge cross-sell and upsell campaign effectiveness and determine the need for mid-stream adjustments or alterations to future campaigns, you will need to monitor insights in real time and over the long term through interactive dashboards.
To Sum It Up
With the explosion in customer data collection, new focus on customer experience and most importantly with breakthrough technologies like machine learning and customer journey analytics, the time is now ripe to give cross-selling and upselling the attention and focus they deserve.
By taking a journey-based, data-driven approach, both B2C and B2B companies can find new cross-sell and upsell opportunities that increase revenue, retain customers and build customer loyalty.