How to use AI to upsell the right customers at the right time

Online shoppers want it all: variety *and* convenience, personalization without privacy transgressions, and a lot more!

They're right to demand it because the tech can make it happen. It's up to us, humans, to leverage the right tools to build that rewarding feeling throughout the customer journey.

As an ecommerce company, you can anticipate your customers' next shopping stage and cater to their individual needs.

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You already have the data and the ecosystem. All you need is the right AI platform to deliver the industry’s holy grail: dynamic customized experiences that provide customers with satisfying shopping sessions.

Maximize the value you provide to customers and the ROI you get from them by infusing AI into your ecommerce flow.

Top 10 challenges in ecommerce today

  1. Nurturing the ideal prospects
  2. Converting shoppers into paying customers
  3. Maintaining customer loyalty
  4. Identifying the most profitable customers to upsell
  5. Improving ROI for remarketing campaigns
  6. Building truly personalized experiences
  7. Reducing digital advertising costs
  8. Increased competition
  9. Scaling customer service with no quality impact
  10. Achieving significant differentiation in the market

80%

of customers are more likely to buy from brands that provide a personalized experience (Epsilon)

85%

of customer interactions will happen without human intervention by 2020 (Plytix)

Why we focus on helping ecommerce companies achieve more with their existing data

We’re big believers in the power of context.

Understanding your customers’ circumstances and priorities is a powerful way to make better decisions, reduce waste (related to time, energy, and budgets), and to create more gratifying experiences.

AI can provide this context by processing large volumes of information and predicting people’s individual behaviors.

When working with practical AI applications, an ecommerce company like yours can scale growth without losing that highly coveted personal touch.

We’re excited to develop MorphL - an AI-as-a-platform - because we have the opportunity to empower companies to work with tech they couldn’t afford until recently.

We believe AI complements and amplifies human expertise, creativity, and judgement.

This is why we’re building AI applications that integrate into existing business flows and don’t require Machine Learning specialists to operate.

Our goal is to help ecommerce extract more value from their existing data

Unify data sources & eliminate data silos

Predict user behavior

Strengthen data integrity

Improve user recognition

Ensure compliance with data protection regulations

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How to use AI to upsell the most profitable customers

In ecommerce, AI plays a key role in reshaping the shopping experience. MorphL enables you to capture and apply scarce knowledge: predictions about your customers’ next shopping stage.

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Process a large volume of signals

We believe the users’ activity (ex. browsed products, number of sessions, time on page, searches, etc.) and history are the most relevant indicators for their probability to convert.

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Extract insights

We go beyond splitting users into converters vs. non-converters and focus on a much more specific targeting method - engage users depending on the most likely shopping stage they’re about to transition to.

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Automatically tailor the shopping experience

You can apply this key competitive advantage to optimize your marketing process, reduce guesswork, and to make better decisions - often automatically.

How you can use it

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Increase Customer Lifetime Value for loyal shoppers

✓ recommend products that match their needs
✓ incentivize additional purchases through highly targeted upsells
✓ provide social proof that matters for shoppers like themselves


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Improve ROI for remarketing campaigns

✓ personalize remarketing offers to match individual users (without the privacy risk)
✓ enhance ad copy by leveraging customer reviews shoppers found useful
✓ reduce intrusiveness by using the right remarketing tactics that work for specific customers

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How MorphL helps

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Shopping stage prediction →

Upsell tactic

Browse products →
Social proof (e.g. "Favorite product for people who shop on this website" or "125 people also bought this product")
Add product to cart →
Pop up with exclusive offer for a slightly better product or a video that shows how the better, more expensive product performs
Checkout →
Recommendation system that features a special offer for accessories or extras

What MorphL delivers: Next shopping stage prediction

The next shopping stage prediction flow for ecommerce companies

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Using an AI-as-a-service platform like MorphL means you can save a lot of time and effort spent pouring over analytics. Insights are automatically integrated into your ecommerce platform and the marketing technologies you use.

What’s more, MorphL predictions are exposed via an API you can easily integrate into your reporting dashboard. Plus, we fully automate the model training and predictions in our infrastructure.

Correlation between the next shopping stage prediction and the main factors that influence it

Use MorphL to identify and understand:

  • How customers shop depending on the season, the promotions you run, and market trends
  • Most popular products and which items shoppers prefer to buy together
  • How product descriptions, search filters, and product classification influence the next shopping stage your customers go into.

What makes AI different from rule-based systems

Rule-based systems
Learning systems (AI)
Use static if-then-that rules
vs.
Can create, discard and change rules based on what they learn
Knowledge is encoded as fixed rules
vs.
Knowledge changes through learning (adaptive intelligence)
New situations that require new rules get the system stuck
vs.
The system can adapt to new situations by creating new rules
The larger the data pool, the bigger the risk of introducing conflicting rules
vs.
The larger the data pool, the better the system becomes by learning from specific situations

Get better at understanding shoppers' behavior

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Data-informed decisions

Make data-informed decisions and design upsell strategies to drive repeat purchases that feel natural for the customer.

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We're here to help!

We’re here to support you with knowledge, guidance, and AI expertise so you can make the most of MorphL and support business growth.

Frequently Asked Questions

Need answers? Have any other questions, please get in touch.

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 779790.