Striped Giraffe Innovation & Strategy GmbH, Lenbachplatz 3, Munich (2026)

28/05/2026

Many B2B companies don’t run slowly because their systems are outdated. 🐌
They run slowly because critical dependencies are still hidden inside everyday processes. 🖇️

A sales rep waits for pricing approval.
Customer service waits for logistics updates.
Procurement waits for contract verification.
The customer waits for everyone.

And suddenly, a company with modern systems still operates at the speed of email threads.

This is where many self-service initiatives fall short.

They are treated as commerce features: order tracking, invoice downloads, reorders, FAQs.

Useful? Absolutely.
Transformational? Not even close.

The real shift begins when self-service becomes part of the operating model.

When a key account manager can approve pricing within defined thresholds, check inventory and delivery risks in real time, access customer-specific contracts instantly, and trigger workflows without opening another ticket.

When customers receive proactive alerts about delays, alternative delivery options, or maintenance recommendations before they even contact support.

That changes more than customer experience.

𝗜𝘁 𝗰𝗵𝗮𝗻𝗴𝗲𝘀 𝗼𝗿𝗴𝗮𝗻𝗶𝘇𝗮𝘁𝗶𝗼𝗻𝗮𝗹 𝘀𝗽𝗲𝗲𝗱.

Robert Gruca, E-Commerce Solution Consultant at Striped Giraffe:

“We increasingly see that the strongest B2B organizations are reducing operational friction by removing unnecessary coordination layers between people, systems, and decisions. And automation plays a major role here.”

But the strategic objective is broader:

“Creating an organization where employees and customers can act autonomously, with reliable real-time information and clearly governed processes.”

That’s a very different conversation from “digital ordering.”

In our latest e-book, we explore how B2B companies are building self-service ecosystems that combine:
🔸 operational autonomy
🔸 process automation
🔸 personalization
🔸 real-time analytics
🔸 scalable architecture

👉 https://www.striped-giraffe.com/en/e-book-self-service-and-automation-in-b2b-ecommerce/

27/05/2026

Many organizations invest heavily in building Data Products.
Very few measure whether those products actually succeed. 📐🎯

Most teams track pipelines, infrastructure, and system performance.
But a Data Product should be evaluated like any other product: by its adoption and impact.

Three categories of metrics matter most.

1️⃣ 𝗔𝗱𝗼𝗽𝘁𝗶𝗼𝗻 𝗺𝗲𝘁𝗿𝗶𝗰𝘀

First, measure whether the product is actually used.

Examples include:
🔸 number of active users
🔸 number of consuming teams
🔸 API calls or queries
🔸 integrations with other systems

If usage is low, the product likely solves the wrong problem.

2️⃣ 𝗥𝗲𝗹𝗶𝗮𝗯𝗶𝗹𝗶𝘁𝘆 𝗺𝗲𝘁𝗿𝗶𝗰𝘀

Consumers depend on predictable data.

Key indicators include:
🔸 data freshness
🔸 SLA adherence
🔸 incident frequency
🔸 data quality scores

Without reliability, adoption quickly collapses.

3️⃣ 𝗕𝘂𝘀𝗶𝗻𝗲𝘀𝘀 𝗶𝗺𝗽𝗮𝗰𝘁 𝗺𝗲𝘁𝗿𝗶𝗰𝘀

Ultimately, Data Products must improve decision-making.

Organizations often track outcomes such as:
🔸 faster decision cycles
🔸 improved forecast accuracy
🔸 better campaign performance
🔸 reduced operational inefficiencies

This is where data initiatives prove their real value.

Łukasz Cempulik, DWH and BI Architect at Striped Giraffe:

"Treating data as a product means accepting one simple principle: success has to be measurable. If you can’t link a Data Product to real usage and business outcomes, it’s very hard to justify its value.”

How does your organization evaluate the impact of its Data Products?
Let us know in the comments. 💬

21/05/2026

Almost every company says automation issues lead to SLA breaches. 61% experience them at least monthly.
And yet, nearly three-quarters still lack end-to-end visibility into their automated business processes. 🫣😬

That’s not a technology gap; it’s a control problem.

A recent global Broadcom study of 500+ executives and IT leaders reveals a pattern that’s hard to ignore:

More automation ➜ more tools ➜ less clarity.

What’s really happening inside many organizations:

🔸 80% run 3+ automation platforms
🔸 74% use 3+ monitoring tools
🔸 74% deal with “alert storms” that obscure root causes

Instead of clarity, teams get noise.
Instead of faster resolution, they get longer investigations.

And the consequences are business-critical:

1️⃣ Issues are detected too late
Most teams only react after something fails.

2️⃣ Impact is unclear
68% can’t tell if a problem will breach an SLA.

3️⃣ Customer experience suffers
88% say SLA breaches directly affect customers.

4️⃣ Costs quietly increase
69% lack the data to properly optimize workloads.

The uncomfortable truth:
Automation has scaled faster than your ability to understand it.

You’ve built highly distributed, event-driven systems —
but visibility has not kept up.

So when something breaks, you don’t just fix issues.
First, you search for them.

This is exactly where the real risk sits today.

If you’re interested in how to close this gap — not by adding more tools, but by making processes truly visible and understandable — we explore this in detail in our latest article:

The Visibility Gap in Automation: Where Processes Lose Transparency
🔗‍️ https://www.striped-giraffe.com/en/blog/the-visibility-gap-in-automation-where-processes-lose-transparency/

20/05/2026

“What’s the best medicine for sinus pain during pregnancy?” 🤔❓
Today, that question is more likely to land in Google or ChatGPT than on an online pharmacy platform.
And that should concern the entire e-pharmacy industry.

Most online pharmacies still operate like traditional retail catalogs:
search by product name, brand, or active ingredient.

But healthcare decisions rarely start that way.

Patients usually begin with:
🔸 symptoms
🔸 uncertainty
🔸 restrictions
🔸 side effects
🔸 interactions
🔸 questions about substitutes or safer alternatives

This is why many pharmacy platforms are quietly evolving beyond transactional e-commerce.

Across Europe, leading players increasingly invest in:
🔹 symptom-based discovery
🔹 AI-assisted search
🔹 substitute and equivalent mapping
🔹 structured product data
🔹 richer medical content
🔹 integrations with telehealth and consultation services

Because the real challenge is no longer putting pharmaceutical products online.
The challenge is helping people navigate healthcare decisions safely, clearly, and with confidence.

And this becomes surprisingly complex in e-pharmacy.

A single product may involve:
🧪 dosage variations
📛 contraindications
💸 reimbursement rules
🌍 country-specific restrictions
🔀 interactions with other medications
⚖️ multiple substitutes and equivalents

Without properly structured and connected data, even the best UX quickly breaks down.

That is why search, discovery, and product information architecture are becoming strategic capabilities in digital pharmacy.

Not just for conversion. But for trust.

Want to explore how data management supports digital pharma and healthcare platforms?

Discover key insights in our free e-book “Data Management in Pharma & Healthcare”:
🔗 https://www.striped-giraffe.com/en/e-book-data-management-in-pharma-healthcare/

18/05/2026

Launching financial products is no longer the problem.
Controlling how they perform is.
And that’s exactly where most banks lose scale. 🤔⬇️

This is the problem we address in our latest article — Part 2 of the series:
“From Financial Institution to Commerce Engine.”

The core insight:
The limiting factor is not speed, channels, or customer access.
It is the loss of control at the moment where product logic, customer data, and decisioning are supposed to come together.

𝗪𝗵𝗮𝘁 𝘆𝗼𝘂’𝗹𝗹 𝗳𝗶𝗻𝗱 𝗶𝗻 𝘁𝗵𝗲 𝗮𝗿𝘁𝗶𝗰𝗹𝗲:

1️⃣ The hidden bottleneck: product governance

🔸 Product logic fragmented across systems
🔸 Pricing, eligibility, and bundling misaligned
🔸 No single control point over the offer

The result: multiple versions of the same product in market.

2️⃣ Why customer data still falls short

🔸 Built for segmentation, not decisions
🔸 Distributed across systems with different timing
🔸 Lacking real-time context

Two different customers — same offer.

3️⃣ Where banks lose control

🔸 Decisions precomputed in batches
🔸 Logic embedded across channels
🔸 Exceptions handled manually

This leads to latency, inconsistency, and missed revenue.

4️⃣ What leading banks do differently

They connect three layers into one system:
🔸 Governed product model (what’s possible)
🔸 Decision-ready customer layer (what’s relevant)
🔸 Real-time decisioning (what’s executed)

Not as separate capabilities — but as a single operating model.

5️⃣ The shift that enables scale

From:
🔸 fragmented logic → governed orchestration
🔸 campaign decisions → real-time decisions
🔸 system constraints → controlled flexibility

This is where financial commerce actually starts to scale.

Want to learn more?

👉 𝗥𝗲𝗮𝗱 𝘁𝗵𝗲 𝗳𝘂𝗹𝗹 𝗮𝗿𝘁𝗶𝗰𝗹𝗲 here:
https://www.striped-giraffe.com/en/blog/from-financial-institution-to-commerce-engine-part-2-the-missing-layer-product-and-customer-orchestration/

13/05/2026

The most successful Data Products don’t start with data.
They start with users 🙋🏻 and the decisions 🔀 those users need to make.
𝗧𝗵𝗮𝘁 𝘀𝗵𝗶𝗳𝘁 𝗰𝗵𝗮𝗻𝗴𝗲𝘀 𝗲𝘃𝗲𝗿𝘆𝘁𝗵𝗶𝗻𝗴 — from how the data is structured to how it is delivered, documented, and maintained.

In real projects, effective Data Products follow a very different design logic.

1️⃣ 𝗦𝘁𝗮𝗿𝘁 𝘄𝗶𝘁𝗵 𝗯𝘂𝘀𝗶𝗻𝗲𝘀𝘀 𝗱𝗲𝗰𝗶𝘀𝗶𝗼𝗻𝘀

Before designing a Data Product, ask a simple question:

What decisions should this data support?

Examples might include:

🔸 pricing optimization
🔸 campaign targeting
🔸 inventory planning
🔸 product performance analysis

Decisions define the product’s purpose.

2️⃣ 𝗜𝗱𝗲𝗻𝘁𝗶𝗳𝘆 𝗿𝗲𝗮𝗹 𝘂𝘀𝗲𝗿𝘀

Every Data Product should have clearly defined consumers.

These might include:

🔸 analytics teams
🔸 operational systems
🔸 machine learning models
🔸 business applications

If nobody depends on the product, adoption will never happen.

3️⃣ 𝗗𝗲𝘀𝗶𝗴𝗻 𝘁𝗵𝗲 𝗽𝗿𝗼𝗱𝘂𝗰𝘁 𝗶𝗻𝘁𝗲𝗿𝗳𝗮𝗰𝗲

Data Products are consumed in different ways.

Common interfaces include:

🔸 curated datasets
🔸 APIs
🔸 semantic layers
🔸 event streams

The interface determines how easily teams can integrate the product into their workflows.

4️⃣ 𝗗𝗲𝗳𝗶𝗻𝗲 𝗮 𝗱𝗮𝘁𝗮 𝗰𝗼𝗻𝘁𝗿𝗮𝗰𝘁

This is where many initiatives fail.

A good Data Product clearly defines:

🔸 schema and definitions
🔸 refresh frequency
🔸 reliability expectations
🔸 versioning rules

Consumers need stability as much as accuracy.

Krzysztof Wiśniewski, VP Data Engineering at Striped Giraffe:

“When Data Products are designed with users, interfaces, and contracts in mind, they stop being passive data assets. They become infrastructure for decision-making.”

🤔 How does your organization design its Data Products?
Let us know in the comments.

11/05/2026

Most banks have already digitized onboarding, channels, and customer journeys. Yet revenue growth remains uneven, hard to replicate, and even harder to scale.
In our latest 𝗯𝗹𝗼𝗴 𝗮𝗿𝘁𝗶𝗰𝗹𝗲 — “Why Digital Growth in Finance Still Stalls” — we unpack the reasons.

𝗧𝗵𝗲 𝗰𝗼𝗿𝗲 𝗶𝗻𝘀𝗶𝗴𝗵𝘁:

Digitization improves access but it does not guarantee monetization.
The constraint sits deeper — in how institutions design and execute commercial decisions.

What you’ll find in the article:

1️⃣ Why growth stalls despite mature digital channel

🔸 Conversion improves selectively
🔸 Cross-sell remains inconsistent
🔸 Embedded finance rarely scales beyond pilots

2️⃣ The structural flaw most teams overlook

🔸 Offers are static
🔸 Pricing is generic
🔸 Decisions lack real-time context

More interactions don’t translate into better outcomes.

3️⃣ What leading institutions do differently

They don’t optimize channels — they restructure decision-making:
🔸 Separate offer logic from core systems
🔸 Centralize product configuration
🔸 Make customer data decision-ready
🔸 Expose capabilities, not systems, via APIs

4️⃣ The shift that changes everything*

From:
🔸 products → offerings
🔸 channels → decisions
🔸 systems → orchestration

This is not an incremental improvement.
It’s a different operating model.

📄 Read the full article here:
https://www.striped-giraffe.com/en/blog/from-financial-institution-to-commerce-engine-part-1-why-digital-growth-in-finance-still-stalls/

07/05/2026

We’re proud to have contributed to a major milestone in digital payments at Hilti. 🎉💯🚀

In mid-April, 𝗙𝗹𝗲𝘅𝗶𝗯𝗹𝗲 𝗣𝗮𝘆𝗺𝗲𝗻𝘁 𝗠𝗲𝘁𝗵𝗼𝗱𝘀 (𝗙𝗣𝗠) went live across 8 European markets — Austria, Czech Republic, Germany, Hungary, Italy, Poland, Slovakia, and Switzerland — expanding the Hilti Online experience with digital payment options like Apple Pay, Google Pay, and local methods such as Przelewy24 in Poland.

What stands out are the immediate post go-live signals shared by Hilti:

🔸 first Google Pay transaction in Hungary within 5 minutes
🔸 first Apple Pay transactions in Czech Republic and Slovakia already on the day of go-live
🔸 early adoption of Przelewy24 in Poland, even without promotion

Most importantly, all of this was achieved with a smooth and controlled go-live — no critical issues, all validation and acceptance criteria met, and cutover and migration executed as planned, supported by a structured post-go-live care model.

We’re pleased to have had the opportunity to support Hilti Group in this project, contributing our experience in integrating payment solutions in B2B e-commerce environments.

From a technical perspective, the core of this solution is SAP Digital Payments, which acts as a central hub between SAP S/4HANA, the e-commerce platform, and an external payment service provider (PSP).

As Damian Woźniak, Technical Architect at Striped Giraffe, explains:

“In this setup, the integration is based on a Direct PSP model, where the frontend communicates directly with the payment service provider (PSP), while SAP Digital Payments orchestrates payment processing in the backend layer, at the level of SAP S/4HANA.

This approach gives flexibility in how payment methods are presented to customers, while keeping PSP-specific logic out of the core backend systems.”

If you’re interested in how this integration model works in practice — and how it compares to alternatives like the Payment Page approach — take a look at our article series.

SAP Digital Payments: Enabling Secure, Scalable, and Future-Ready Payment Processes
👉 https://www.striped-giraffe.com/en/blog/sap-digital-payments-enabling-secure-scalable-and-future-ready-payment-processes/

How to Integrate SAP Digital Payments into Your E-Commerce Architecture
👉 https://www.striped-giraffe.com/en/blog/how-to-integrate-sap-digital-payments-into-your-e-commerce-architecture/

hashtag

04/05/2026

Headless commerce is often associated with speed ᯓ🏃🏻‍♀️‍➡️, flexibility ⁀🤸‍♂️, and lower long-term cost 📉💰.
And those promises are 𝗿𝗲𝗮𝗹 — but 𝗰𝗼𝗻𝗱𝗶𝘁𝗶𝗼𝗻𝗮𝗹.

In practice, headless delivers 𝗼𝗽𝘁𝗶𝗼𝗻𝗮𝗹𝗶𝘁𝘆.
And optionality means more choices, more paths, and more responsibility.

We’ve seen headless commerce create 𝗿𝗲𝗮𝗹 𝘀𝘁𝗿𝗮𝘁𝗲𝗴𝗶𝗰 𝗹𝗲𝘃𝗲𝗿𝗮𝗴𝗲.
We’ve also seen it quietly increase coordination effort, operating complexity, and cost.

The difference was rarely the technology itself.
It was 𝗼𝗿𝗴𝗮𝗻𝗶𝘇𝗮𝘁𝗶𝗼𝗻𝗮𝗹 𝗺𝗮𝘁𝘂𝗿𝗶𝘁𝘆.

As Sophia Weiss, VP Digital Experience at Striped Giraffe, explains:
“Headless creates room for better decisions — but only organizations prepared to make and own those decisions benefit from it.”

Headless commerce pays off when companies are ready to operate across teams, releases, and vendors.

If you’re considering headless commerce as a strategic move, our latest blog article explains when this commitment creates value — and when it doesn’t.

🔗‍️ https://www.striped-giraffe.com/en/blog/headless-commerce-between-promise-and-reality/

29/04/2026

Most conversations about GenAI in commerce still revolve around retail.
Meanwhile, something equally significant has been unfolding in B2B, much more quietly. And the data now makes it very clear. 💡⬇️

Forrester’s latest research shows that nearly all B2B buyers (94%) already use genAI in at least one area of their purchasing process.

This spans the entire journey: from discovering solutions, through evaluation, to final decision-making.

What’s even more striking:
‼️ Business buyers now rate genAI as 𝗺𝗼𝗿𝗲 𝗶𝗻𝗳𝗹𝘂𝗲𝗻𝘁𝗶𝗮𝗹 𝘁𝗵𝗮𝗻 𝘁𝗿𝗮𝗱𝗶𝘁𝗶𝗼𝗻𝗮𝗹 𝘀𝗼𝘂𝗿𝗰𝗲𝘀, including vendor websites and product experts.

And the shift is accelerating: B2B buyers use AI to evaluate more options, run deeper analyses, and reach decisions faster, even in high-value purchases.

👉 𝗪𝗵𝗲𝗿𝗲 𝗔𝗜 𝗮𝗰𝘁𝘂𝗮𝗹𝗹𝘆 𝘀𝗵𝗼𝘄𝘀 𝘂𝗽 𝗶𝗻 𝗕𝟮𝗕 𝗯𝘂𝘆𝗶𝗻𝗴

Forrester’s data reveals a clear pattern.

B2B buyers most often use GenAI at the very start of the journey — to navigate complexity and build context.

🔸 gathering product best practices (57%)
🔸 analyzing internal data about the purchase (56%)
🔸 comparing product strengths and weaknesses (55%)
🔸 researching specific products (54%)
🔸 checking pricing and vendors (52%)

This is where AI delivers immediate value — faster orientation, broader perspective, better-informed starting points.

But AI’s role doesn’t stop there.

A second layer shows how 𝗴𝗲𝗻𝗔𝗜 𝗶𝗻𝗰𝗿𝗲𝗮𝘀𝗶𝗻𝗴𝗹𝘆 𝘀𝘂𝗽𝗽𝗼𝗿𝘁𝘀 𝗲𝘃𝗮𝗹𝘂𝗮𝘁𝗶𝗼𝗻 𝗮𝗻𝗱 𝗱𝗲𝗰𝗶𝘀𝗶𝗼𝗻-𝗺𝗮𝗸𝗶𝗻𝗴:

🔸 supporting purchase decisions (51%)
🔸 shortlisting providers (49%)
🔸 analyzing RFP responses (48%)
🔸 building business cases (47%)
🔸 generating requirements and contract terms (47%)

This shows that AI increasingly moves beyond informing buyers. It begins to structure decision logic and, in some cases, execute it.

This is exactly the shift we explore in our latest e-book “𝗔𝗜 𝗶𝗻 𝗘-𝗖𝗼𝗺𝗺𝗲𝗿𝗰𝗲”: How systems start to take over parts of decision-making and purchasing processes.

🔗 https://www.striped-giraffe.com/en/e-book-ai-in-ecommerce/

Striped Giraffe Innovation & Strategy GmbH

28/05/2026

27/05/2026

21/05/2026

20/05/2026

18/05/2026

13/05/2026

11/05/2026

07/05/2026

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29/04/2026

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