Personalisation has become a familiar feature of online retail. Product recommendations, abandoned-basket messages, personalised offers and individually tailored emails are now commonplace. More sophisticated retailers are extending personalisation across websites, mobile, SMS and the post-purchase journey. But greater technical capability does not automatically create a better customer experience.
Poorly implemented personalisation can be irrelevant, repetitive or intrusive. It can recommend products customers have already purchased, offer unnecessary discounts or create inconsistent experiences between different channels.
For eCommerce buyers, the real objective should therefore be relevance rather than personalisation itself.
The right technology should help retailers use customer, behavioural and transactional data to make shopping easier, surface useful products and communicate at appropriate moments, while giving teams appropriate control over data, commercial rules and measurement.
This guide examines what retailers should compare when evaluating eCommerce personalisation software and specialist technology partners.
At a Glance: What to Compare
| Capability | What Buyers Should Consider |
|---|---|
| Customer data | Behavioural, transactional and profile information |
| Product recommendations | Relevance, algorithms and merchandising control |
| Segmentation | Real-time and behavioural audiences |
| Website personalisation | Content, banners, navigation and recommendations |
| Cross-channel | Email, web, mobile, SMS and other touchpoints |
| Automation | Triggers based on customer behaviour |
| Offers | Discounts, incentives and promotional targeting |
| Integrations | eCommerce, CRM, CDP and marketing platforms |
| Privacy | Consent, transparency and data governance |
| Measurement | Conversion, AOV, revenue, retention and incremental impact |
What Is eCommerce Personalisation?
eCommerce personalisation uses information about customers and their behaviour to adapt the shopping experience.
That information might include:
- Products viewed
- Searches
- Purchase history
- Basket contents
- Location
- Customer status
- Product preferences
- Email engagement
- Device
- Previous interactions
The resulting experience could be as simple as displaying recently viewed products or as sophisticated as dynamically changing recommendations, offers and communications throughout the customer journey.
Personalisation can operate across:
Discovery → consideration → basket → checkout → post-purchase → retention
The important point for buyers is that these experiences depend on good underlying data.
If the platform does not understand the customer accurately, the personalisation built on top of that information is unlikely to be useful.
eCommerce Personalisation Software
eCommerce personalisation software can range from individual recommendation engines to broader platforms combining customer data, segmentation, automation and cross-channel marketing.
Capabilities may include:
- Product recommendations
- Behavioural targeting
- Dynamic website content
- Personalised search
- Email personalisation
- Abandoned-basket messaging
- Browse-abandonment campaigns
- Location-based content
- Customer segmentation
- Personalised incentives
For example, current Dotdigital functionality can use website behaviour, purchase history and other customer information to drive recommendations, personalised web and email content and triggered messaging.
The procurement challenge is determining which capabilities will genuinely improve the customer journey.
A retailer with thousands of products may derive considerable value from sophisticated recommendations.
A business selling a small number of high-value products may benefit more from customer segmentation and personalised content.
Buyer Tip
Start with the customer journey, not the feature list.
Identify where customers currently encounter friction or irrelevant experiences, then determine whether personalisation can solve those problems.
Personalised Product Recommendations
Product recommendations are one of the most familiar forms of eCommerce personalisation.
Examples include:
- You may also like
- Frequently bought together
- Similar products
- Complete the look
- Recommended for you
- Recently viewed
- Replenishment suggestions
The sophistication lies in deciding which customer should see which product at which moment.
Recommendation engines might use:
- Browsing history
- Purchase history
- Similar customer behaviour
- Product attributes
- Basket contents
- Availability
- Customer preferences
Buyers should also investigate the degree of merchandising control available.
Retail teams may need to exclude:
- Out-of-stock products
- Low-margin products
- Particular brands
- Inappropriate combinations
- Products already purchased
The strongest system should combine automated relevance with sensible commercial rules.
Behavioural Personalisation
Customer behaviour can provide useful indications of intent.
For example:
Customer A: First visit, browsing a product category.
Customer B: Third visit this week, repeatedly viewing one product.
Customer C: Has added the product to their basket but not purchased.
Treating all three visitors identically misses important context.
Behavioural personalisation can allow retailers to create different experiences according to signals such as:
- Number of visits
- Pages viewed
- Products browsed
- Basket activity
- Previous purchases
- Time since last purchase
- Customer value
This can make communications more relevant without necessarily requiring retailers to know everything about an individual.
Real-Time Personalisation
Timing matters. A customer who was interested in a product six months ago may no longer be interested today.
Modern personalisation platforms can process behavioural signals quickly enough to adapt experiences during or shortly after a customer session.
That might enable:
- Updated recommendations
- Basket reminders
- Browse-abandonment messages
- Back-in-stock alerts
- Price-change notifications
- Relevant website content
But buyers should ask what suppliers mean by real time.
Some changes may happen during the current website session, while others depend on data synchronisation between different platforms.
Understanding that latency is particularly important when multiple systems are involved.
Cross-Channel Personalisation
Customers rarely think about a retailer’s technology stack.
They simply experience the brand.
A shopper might:
Browse on mobile → open an email → visit on desktop → purchase → receive an SMS
If each channel operates independently, personalisation can become fragmented.
The customer might receive an abandoned-basket email after purchasing the product, for example, or continue seeing acquisition offers despite already becoming a customer.
Cross-channel personalisation attempts to create greater continuity.
Buyers should therefore ask whether customer information can be shared between:
- Website
- SMS
- Mobile
- CRM
- Customer service
- Loyalty
- Advertising
The objective is not necessarily to personalise every channel.
It is to avoid different channels behaving as though they are dealing with different people.
Customer Data and Personalisation
The quality of personalisation is closely linked to the quality of customer data.
Useful information may come from:
Behavioural data
What customers browse, search and click.
Transactional data
What they purchase, return and spend.
Profile data
Information customers have supplied directly.
Engagement data
How they interact with email, SMS and other communications.
Product data
Categories, brands, attributes, availability and pricing.
Connecting these datasets can improve relevance, but buyers should resist assuming that more data automatically equals better personalisation.
Data should have a clear purpose.
Personalisation Principle
Collect and use the information required to improve the experience, not information simply because the technology makes it possible.
Personalisation and Privacy
Personalisation inevitably raises questions around customer data.
Retailers need to understand:
- What information is collected
- Why it is collected
- How it is processed
- Which technologies track behaviour
- Whether information is shared
- How long it is retained
- How customers can exercise their rights
The ICO’s guidance on data protection principles stresses that personal data should be adequate, relevant and limited to what is necessary for the purpose for which it is processed.
ICO – Data Minimisation – https://ico.org.uk/for-organisations/uk-gdpr-guidance-and-resources/data-protection-principles/a-guide-to-the-data-protection-principles/
This is particularly relevant when retailers consider increasingly sophisticated behavioural targeting.
Buyers should involve privacy and data-governance teams early rather than attempting to resolve these questions after technology selection.
Personalised Offers and Incentives
Personalisation can also determine whether a customer needs an incentive at all.
Blanket discounting can damage margin by giving offers to customers who may have purchased anyway.
More targeted approaches might consider:
- Customer intent
- Basket value
- Customer value
- Purchase history
- Product margin
- Loyalty
- Abandonment behaviour
Platforms such as RevLifter, for example, use segmentation and behavioural signals to target different offers and incentives rather than presenting every visitor with the same promotion.
For buyers, the commercial question is important:
Did the personalisation create additional value, or simply discount a transaction that would already have happened?
That distinction should inform measurement.
Personalisation Without Over-Personalisation
There is a point at which relevance can become intrusive.
Consider:
Useful: “You bought running shoes recently, you may need these compatible accessories.”
versus
Uncomfortable: A highly specific message revealing unexpectedly detailed knowledge about an individual’s behaviour.
Retailers should consider how personalisation will feel from the customer’s perspective.
Useful principles include:
- Make relevance obvious
- Avoid unnecessarily sensitive inference
- Don’t repeatedly target customers with the same message
- Recognise when a purchase has already happened
- Give customers appropriate control
- Test experiences with real users
Good personalisation should often feel effortless rather than conspicuous.
Integration with the eCommerce Technology Stack
Personalisation rarely operates independently.
Platforms may need to connect with:
- eCommerce platforms
- CRM
- CDP
- Email marketing
- SMS
- Loyalty platforms
- Product information management
- Inventory
- Customer service
- Analytics
Buyers should investigate whether integrations are:
- Native
- API-based
- Custom
- Real-time
- Batch synchronised
Implementation effort matters. A platform with impressive capabilities can become expensive if every useful function requires custom development.
Ask suppliers to map exactly how their technology would connect to the existing environment before making a decision.
Personalisation and Product Availability
A recommendation is only useful if the product is available.
Retailers should therefore investigate whether personalisation platforms can incorporate:
- Current inventory
- Store availability
- Size availability
- Delivery location
- Product status
- Price changes
This prevents frustrating experiences where a customer clicks a highly relevant recommendation only to discover the product cannot be purchased.
For businesses with complex inventories, connecting personalisation to current product data can be just as important as understanding the customer.
Measuring Personalisation Performance
Personalisation technology should produce measurable commercial outcomes.
Potential metrics include:
- Conversion rate
- Average order value
- Click-through rate
- Revenue per visitor
- Basket abandonment
- Repeat purchase
- Customer lifetime value
- Engagement
- Retention
However, buyers should distinguish correlation from incremental impact.
If customers receiving personalised recommendations spend more, was that because of the recommendations, or were those customers already more likely to purchase?
A/B testing and control groups can help establish the difference.
Measurement Insight
Don’t ask only:
“How much revenue touched personalisation?”
Ask:
“How much additional revenue did personalisation create?”
That is a much more useful measure of ROI.
AI and eCommerce Personalisation
Artificial intelligence and machine learning increasingly support personalisation through capabilities such as:
- Product recommendations
- Predictive segmentation
- Customer intent analysis
- Offer optimisation
- Next-best-action models
- Automated content selection
AI can help identify patterns that would be difficult to manage manually across large customer and product datasets.
But automated decisions still need appropriate oversight.
Retail teams should understand:
- Which data influences recommendations
- Which commercial rules can override algorithms
- How outcomes are tested
- How inappropriate recommendations are prevented
- How performance is measured
The aim should be better relevance, not simply greater automation.
Choosing an eCommerce Personalisation Partner
The supplier market spans software platforms, agencies, digital consultancies and specialist technology providers.
That means buyers may need different types of support.
A retailer might require:
Technology only
An internal team manages strategy and implementation.
Technology + implementation
A specialist configures and integrates the platform.
Managed personalisation
An external partner supports strategy, campaigns, optimisation and ongoing delivery.
Before procurement, establish which skills already exist internally.
This prevents businesses from buying powerful technology without the resources required to use it effectively.
What Should Buyers Compare?
Personalisation capabilities
Which parts of the customer journey can be personalised?
Customer data
Which behavioural, transactional and profile information can be used?
Recommendations
How are products selected and what merchandising controls are available?
Segmentation
Can audiences change dynamically according to behaviour?
Cross-channel support
Can experiences connect web, email, SMS and mobile?
Integration
How easily will the technology connect with the existing stack?
Privacy
What controls support responsible customer-data use?
Testing
Can teams run experiments and control groups?
Reporting
Can incremental commercial impact be measured?
Services
How much implementation and optimisation support does the supplier provide?
Questions to Ask Personalisation Suppliers
- Which parts of the customer journey can your platform personalise?
- Which customer data sources can it use?
- How quickly does behavioural data become available?
- How are product recommendations generated?
- Can merchandising teams override automated recommendations?
- Can stock availability influence recommendations?
- Which eCommerce platforms do you integrate with?
- Which CRM and marketing platforms are supported?
- Can personalisation operate across web, email, SMS and mobile?
- How are anonymous visitors treated?
- What consent and privacy controls are available?
- Can we control data retention?
- How are personalised incentives targeted?
- What testing capabilities are included?
- Can we measure incremental revenue rather than attributed revenue?
- How much technical resource is required for implementation?
- What ongoing optimisation support do you provide?
Frequently Asked Questions
What is eCommerce personalisation?
eCommerce personalisation uses customer, behavioural and transactional information to tailor products, content, offers and communications to individual shoppers or relevant audience groups.
What is eCommerce personalisation software?
It is technology used to create personalised digital-shopping experiences, potentially including product recommendations, behavioural targeting, dynamic content, segmentation and triggered communications.
How does eCommerce personalisation work?
Platforms analyse information such as browsing behaviour, purchases, customer profiles and product data and apply rules or algorithms to determine which experience or content to present.
Can eCommerce personalisation increase conversions?
Relevant recommendations and experiences can support conversion, but retailers should use testing to determine the incremental impact of personalisation rather than assuming every personalised interaction generates additional revenue.
Does personalisation require AI?
No. Personalisation can use straightforward rules and segmentation, although AI and machine learning can support more sophisticated recommendations and predictive targeting.
What data is needed for personalisation?
This depends on the use case. Behavioural, transactional, customer-profile and product information can all be useful, but retailers should collect and process data for clearly defined purposes.
Product Guide
Personalisation can span strategy, customer data, digital experience, marketing automation, eCommerce development and specialist optimisation. The following providers offer capabilities across different parts of that ecosystem and are present at the upcoming eCommerce Forum.
Featured Suppliers
Alchemy Network Ltd
Digital and technology partner supporting businesses with digital transformation, customer experience and technology solutions, helping organisations connect platforms and create more effective digital journeys.
Website: https://www.alchemy-network.co.uk/
Arsenalia
International group of specialist companies supporting digital transformation, customer experience, commerce, data and technology. Its capabilities can help brands connect digital platforms and create more integrated, personalised customer experiences.
Website: https://www.arsenalia.com/en
Brevo
Customer relationship and marketing platform bringing together email, SMS, automation, customer data and sales capabilities. It enables businesses to segment audiences and deliver targeted communications across customer journeys.
Website: https://www.brevo.com/
CTI Digital
UK digital agency specialising in digital experience, eCommerce, development and digital transformation. CTI Digital works with organisations to design and optimise customer journeys while integrating the platforms and data underpinning digital experiences.
Website: https://www.ctidigital.com/
Culina
UK logistics and supply chain specialist supporting brands and retailers across warehousing, distribution and related operations. Within an eCommerce environment, fulfilment and logistics data can play an important role in creating accurate delivery and post-purchase customer experiences.
Website: https://www.culina.co.uk/
Dotdigital EMEA Ltd
Customer experience and marketing automation platform supporting email, SMS and cross-channel engagement. Dotdigital’s personalisation capabilities include behavioural targeting, product recommendations, triggered messaging and personalised website and email content.
Website: https://dotdigital.com/
ICS-digital
International digital marketing agency providing multilingual and international digital strategy, content, search and marketing services, helping brands adapt customer acquisition and engagement for different audiences and markets.
Website: https://www.ics-digital.com/
Magebit
eCommerce agency specialising in the design, development, optimisation and support of online retail platforms. Its capabilities span eCommerce development, integrations and customer-experience optimisation for retailers operating complex digital stores.
Website: https://magebit.com/
Merx
Digital commerce specialist supporting brands with eCommerce strategy, technology and customer experiences, helping organisations develop and optimise digital journeys around their individual commercial requirements.
Website: https://www.hellomerx.com/
On Tap OÜ
eCommerce development specialist with extensive experience supporting online retailers with platform development, integrations, optimisation and ongoing technical services.
Website: https://www.ontapgroup.com/
RevLifter
eCommerce personalisation technology provider specialising in intelligent offers and incentives. Its platform uses customer intent, behavioural signals, rules and segmentation to target promotions and experiences, helping retailers improve conversion while reducing unnecessary discounting.
Website: https://www.revlifter.com/
Sozo Design
Digital agency providing web design, eCommerce, development and digital marketing services, supporting businesses in creating and improving online customer experiences.
Website: https://sozodesign.co.uk/
VINSINFO
Technology and digital solutions provider supporting organisations across software, commerce and digital transformation, including the development and integration of platforms underpinning online customer experiences.
Website: https://vinsinfo.com/
Explore eCommerce Personalisation Solutions
The objective of personalisation should not be to prove how much a retailer knows about its customers.
It should be to make the shopping experience more useful.
That might mean helping someone find the right product faster, removing an irrelevant offer, recognising an existing customer, sending a timely replenishment reminder or ensuring communications reflect what has already happened elsewhere in the journey.
For buyers, this makes data quality, integration, control and measurement every bit as important as the sophistication of the personalisation algorithm.
The eCommerce Forum connects senior eCommerce, digital and payments professionals with carefully selected technology and service providers through a programme of pre-arranged one-to-one meetings.
Explore eCommerce personalisation solutions, compare specialist providers and discover technologies and services that can help turn customer data into more relevant, measurable digital experiences.
Sources
- Information Commissioner’s Office – Data Protection Principles – https://ico.org.uk/for-organisations/uk-gdpr-guidance-and-resources/data-protection-principles/a-guide-to-the-data-protection-principles/
- Information Commissioner’s Office – Data Minimisation – https://ico.org.uk/for-organisations/uk-gdpr-guidance-and-resources/data-protection-principles/a-guide-to-the-data-protection-principles/
- Information Commissioner’s Office – Cookies and Similar Technologies – https://ico.org.uk/for-organisations/direct-marketing-and-privacy-and-electronic-communications/guide-to-pecr/cookies-and-similar-technologies/
- Dotdigital – eCommerce Personalisation Guide – https://dotdigital.com/blog/the-complete-guide-to-ecommerce-personalization/
- Dotdigital – Personalisation – https://dotdigital.com/personalization/
- RevLifter – Intelligent Offer Platform – https://www.revlifter.com/platform
