We are proud to share an information security update from Remarkable!

We’ve just completed another highly successful Continuing Assessment Visit with NQA for our ISO 27001:2022 certification, and we’re delighted to say that we continue to meet the highest standards for information security management. The audit report highlighted that “The organisation’s context is well defined, leadership has been effectively demonstrated and commitment levels are fully evident.”

As we continue to mature our Information Security Management System, this assessment is also a valuable opportunity to reflect on the progress we’ve made over the past year. Our ongoing commitment to maintaining a robust security posture includes regular internal audits, structured risk assessments, proactive monitoring, and continuous improvement initiatives — all of which help ensure that our security controls remain aligned with both ISO 27001:2022 and industry best practice.

Marie Heinsen, VP for Agency Services, said “A huge thank you to everyone involved — maintaining this certification is truly a cross-team effort, and it reflects our commitment to protecting our clients’ data with rigour and care.”

Alongside this, we’ve also renewed our Cyber Essentials certification, strengthening our resilience even further and ensuring we continue to demonstrate robust security controls across our digital environment.

These accreditations are more than just badges — they inform our processes, enhance our operations, reinforce trust, support our clients, and help us stay ahead in a landscape where cyber threats continue to evolve. This year, we’ve also focused on broadening awareness and training across the business, ensuring teams have the knowledge they need to identify risks early and uphold best-in-class security practices. Our ISMS places great emphasis on staff understanding their responsibilities, from secure access control to incident reporting, helping us maintain a culture where security is embedded into everyday decision-making.

Sangeeta Brady, COO said “I’m incredibly proud of the team for their continued dedication and discipline throughout this process. The team really do care about the security of both Remarkable and our clients’ data”.

As organisations increasingly navigate complex digital ecosystems, the need for strong, adaptable security frameworks has never been greater. Whether you’re looking to assure stakeholders, meet growing regulatory expectations, or simply build confidence in the resilience of your systems, investing in solid security foundations can unlock long-term value and reduce operational risk.

If your organisation is looking to strengthen its digital maturity, enhance security, or accelerate growth through smarter use of technology, Remarkable’s digital consultancy team is here to help.

Get in touch to find out how we can support your next step forward.

The post Remarkable Celebrates Security Achievement appeared first on Remarkable.

FOR IMMEDIATE RELEASE  

Remarkable’s Top 20 UK Banks Digital Maturity Report 2026 finds a sector investing heavily in visibility while neglecting the infrastructure that drives revenue – and a challenger bank leading the entire industry  

LONDON, 5 March 2026  – Customer experience consultancy Remarkable today publishes the Top 20 UK Banks Digital Maturity Report 2026 – a comprehensive independent analysis of digital marketing performance across the UK retail banking sector. The research reveals a widening gap between the millions being invested in Digital infrastructure and the outcomes those investments are producing.  

Twenty banks were assessed across ten dimensions, from strategic commitment and search performance to customer satisfaction and real-world switching behaviour. Every metric was drawn from independent third-party sources. No bank was asked to self-report.  

The headline finding is stark: a few banks are building scalable digital capability. The rest are incurring costs.  

Monzo leads the overall rankings, achieving a score of 73.7%. The challenger bank, which now serves more than 10 million UK customers, recorded 82% overall satisfaction and 87% satisfaction for online and mobile banking. Lloyds and Starling Bank rank second and third respectively. The results suggest challenger banks are no longer disruptors — they are increasingly setting the standard for digital banking performance. 

Five findings that every bank should pay attention to:  

1. The gap between digital investment and customer outcomes is wider than the sector acknowledges. HSBC and Barclays both score 100% on marketing technology. Both also score below 62% on customer satisfaction. Across the study, the correlation between what banks spend on digital and what customers feel is weaker than any boardroom should be comfortable with. Infrastructure is necessary. It is not sufficient.
2. Content has stopped working as a differentiator. Nineteen of twenty banks produce the same content formats at broadly comparable quality. When an entire sector converges on identical outputs, content ceases to generate competitive advantage and becomes a cost of presence. Monzo is the only bank in the study producing video content – a format that 19 of 20 of its competitors have declined to invest in despite clear consumer appetite for it.
3. Paid search is haemorrhaging budget at the top of the market. Paid search spending is rapidly increasing, but the returns are declining. Santander is estimated to spend £5.62 million per month on paid search, generating fewer than 45,000 clicks, which leads to a cost per click of over £100. In comparison, First Direct achieves almost 100,000 clicks from only 408 keywords, showing that targeted strategies can be more effective than larger campaigns.
4. Switching data exposes retention problems that satisfaction surveys do not. Several banks report acceptable NPS-like satisfaction scores but lose thousands of customers each quarter through CASS data. Santander lost nearly 20,000 net customers in Q3 2025 – the largest net loss in the study – while spending an estimated £5.62 million per month on paid search. Halifax lost over 17,000 in the same period. Meanwhile, Nationwide gained a net 41,000 switchers in Q3 2025, outperforming every high street bank and every digital challenger, suggesting its proposition is landing in a way its modest marketing spend does not fully explain. RBS carries an overall satisfaction score below 50% – the only bank in the study to fall below that threshold - representing a retention risk that no digital investment programme has yet resolved.
5. Nine banks are failing a basic legal standard on their websites. Nine out of twenty banks fail their Core Web Vitals assessment. Only two banks – Monzo and Santander – offer multilingual capabilities, leaving eighteen banks effectively inaccessible to the eight million UK residents who speak a language other than English as their first language. With the European Accessibility Act now in force, low accessibility scores are no longer a performance issue. They are a compliance one.  

For banks already investing heavily in digital transformation, the report raises an uncomfortable question: are those investments actually improving customer experience and retention? 

Paul Stephen, CGO of Remarkable, said:   

“UK banking has undergone more digital change in the past decade than in the previous fifty years combined. Branch numbers have fallen by over 40% since 2015. Mobile banking among adults under 55 has exceeded 80%. By every traditional measure, this is a digitally mature industry. What this report reveals is that the infrastructure banks have built to attract and convert customers has not kept pace with the transformation they have been announcing. The banks treating this report as a benchmarking exercise will find it useful. The banks treating it as a brief will find it transformative. The difference between those two responses is the same difference that separates the top five from the rest of the table.” 

The Top 20 UK Banks Digital Maturity Report 2026 is available to download here. The full report includes individual bank profiles, metric-by-metric analysis, a top five deep dive, and recommendations and opportunities for every institution assessed.  

About Remarkable  
Remarkable is a customer experience consultancy helping organisations achieve measurable digital growth. Through its Revolution programme—a perpetual, evidence-based approach to digital transformation—Remarkable works with clients across financial services, manufacturing and beyond to build the cross-channel capabilities that drive sustainable commercial performance. Remarkable has been navigating the digital landscape for over 50 years.  

Media Contact  
Harriet Barley, Head of Marketing and Communications, Remarkable
harriet.barley@remarkable.global  

Data was collected during February 2026. Scores reflect a specific point in time and may have changed since then. Methodology details are available on request.  

The post UK Banks are spending millions on digital. New research reveals it isn’t working.   appeared first on Remarkable.

Incumbents now make up seven of the top ten banks by feature score. 11:FS benchmarking from August 2025 puts NatWest and RBS at 93 out of 100, within striking distance of Monzo’s 98. Spending insights, instant notifications, budgeting tools, savings pots. All present and accounted for.

The satisfaction gap persists anyway. Starling, Monzo, and First Direct top the Which? 2025 rankings. Barclays, Lloyds, and NatWest lag behind.

But it’s not because features are missing.

Something else is.

The metric nobody tracks

The gap isn’t about what a bank offers. It’s about how quickly a bank spots friction and fixes it. McKinsey research shows that FinTechs deploy features every two to six months. Incumbents take twelve to eighteen. Challengers didn’t succeed because they shipped a better budgeting tool in 2019. They succeeded because they’ve shipped a dozen improvements since, each addressing what customers struggled with.

The cycle time between “we identified a problem” and “customers experience the fix” explains competitive outcomes more starkly than any feature checklist.

For a challenger, that cycle might be days or weeks. For most incumbents, it stretches to quarters or years.

This matters because customer expectations keep moving. Salesforce’s State of the Connected Customer research shows 73% of customers expect companies to understand their unique needs, up from 66% in 2020. Zendesk’s 2025 data shows 63% will switch to a competitor after a single poor experience.

A bank that improves slowly falls behind even as it improves. The target moves faster than the progress.

The depressingly familiar pattern

Transformation programmes launch with executive sponsorship and a dedicated budget. Quick wins are plentiful in the first twelve months, and with the wins comes excitement.

Then the friction builds.

Legacy systems make changes expensive, siloed teams disagree on priorities, and compliance reviews add weeks to every release. The programme doesn’t immediately fail. It just slows down until the gap between ambition and execution regresses to the status quo.

BCG demonstrated that failure rates accelerate to 50% within two years without sustained sponsorship. It’s a slow, sad death for the programme that hurts both the customer and internal teams.

You can’t ‘Aldi’ your way out of the situation

The instinct to copy features and experiences is understandable. If Monzo’s onboarding takes three minutes, make yours take three minutes. And it works up to a point. But by the time you’ve replicated one innovation, the challenger has shipped three more.

RBS learned this with Bó. The app looked modern enough, but legacy back-end systems constrained what could change quickly, and internal culture couldn’t support rapid iteration. Six months later, Bó was shut down.

A modern interface couldn’t compensate for the underlying structure.

Some challenger advantages come from business model choices that incumbents can’t easily replicate – free accounts, minimal fees, and higher savings rates. These work for challengers operating on venture capital with long runways to profitability. But an established bank copying those economics would cannibalise its own revenue.

The strategic response can’t be imitation. That won’t work. The only response is building a different kind of advantage.

AI levels the playing field, if it’s embraced

NatWest reorganised its customer experience work around what they call “customer missions”. Small, cross-functional teams focused on specific moments (like a customer realising they’re paying unnecessary fees). Data specialists, product managers, and marketers share an AI toolset that surfaces friction, generates intervention ideas, and launches tests without waiting for engineering sprints.

The results are genuinely impressive, with 60% of sales now prompted by next-best-action algorithms. More importantly, customer lifetime value has doubled, built on 3.6 billion personalised interactions per year. Because of this, a self-serve journey deployment that once took six weeks now takes one to two.

It isn’t just NatWest. Lloyds has deployed 18 generative AI systems to support faster experimentation, and BBVA runs over a thousand A/B tests annually. What connects these examples is a specific view of AI’s purpose – powering an internal engine for detecting problems faster, testing solutions faster, and deploying changes faster.

Not building a poorly performing customer-facing chatbot.

Using structural advantages…to your advantage

Incumbents have options that challengers don’t, but most banks treat them as legacy burdens rather than sources of differentiation.

Data is the obvious opportunity. A bank with ten million customers across current accounts, mortgages, savings, and credit cards has behavioural information no challenger can match. Challengers see spending patterns. Incumbents could see spending patterns, income stability, debt levels, savings habits, and life-stage transitions all at once.

This only creates an advantage if it’s unified into a real-time view that teams can use. NatWest’s missions work because they’re built on that 360-degree view. Most incumbents have the data fragmented across product silos, so the advantage exists in theory but not in practice.

Then there’s the hybrid model. Customers still value face-to-face advice for complex decisions even as everyday transactions move digital. Incumbents can offer digital convenience for routine banking and expert guidance when it matters. But challengers structurally cannot replicate that within their financial model.

The commercial case for moving faster

DORA research shows high-performing teams that deploy more frequently are twice as likely to exceed organisational performance goals. Whether speed causes the improvement or correlates with other capabilities is hard to determine. Banks investing in agile transformation typically invest in leadership, architecture modernisation, and customer analytics simultaneously.

But the practical implication is the same. Iteration speed appears to be a leading indicator of success.

Bain’s research on customer advocacy shows promoters generate roughly £8,000 more lifetime value than detractors, make seven times as many referrals, allocate 45% more deposits, and buy 25% more products. Better experiences drive higher retention, and higher retention increases share of wallet. All this funds further investment and, as you’d expect, the economics compound.

Banks that improve fastest pull ahead. Banks that stall fall into a cycle where customer defections reduce the resources available to prevent further defections.

The inertia objection

The obvious counterargument is that if switching is so rare, why does any of this matter? It’s true that fifty-eight percent of customers perceive switching as a hassle, fifty-five percent find it stressful, and CASS volumes sit at around one million switches annually.

Inertia protects mediocrity temporarily. Not permanently.

Younger customers forming primary banking relationships now don’t have the same tolerance for friction, because they’ve grown up switching apps weekly. This helps to explain why half of UK adults now hold at least one neobank relationship, up from 16% in 2018. Equally, the introduction of open banking and faster payments has made multi-banking easier, even without full switching.

A customer who stays but moves their savings to Chase, their international transfers to Wise, and recommends Monzo to their children is still retained in your metrics.

They’re just worth progressively less.

Where the competition plays out

The feature gap has largely closed. The hope that challengers would burn out hasn’t materialised. Monzo posted its first profit in 2024, doubled revenue to £880 million, and grew deposits 88% to £11.2 billion, while Starling has seen four consecutive years of profitability.

Chase UK has acquired 2.5 million customers and tops service satisfaction rankings, and Nationwide led current account switches in Q2 2025. The threat is no longer just nimble startups but digitally native offerings from players with both speed and scale.

The remaining gap is CX velocity. It’s the ability to detect what’s frustrating customers, test fixes, and deploy improvements before the competition does. That requires investment in data infrastructure, experimentation platforms, and cross-functional teams empowered to act on what they learn.

The banks making this shift aren’t waiting for a perfect plan. Instead, they’re building a culture that improves continuously because they know that’s how you sustain an advantage.

Everyone else faces a slower decline. Not a crisis or a mass exodus. Just a gradual fade, where customers stay on paper, but their deposits, their referrals, and their children’s first accounts go somewhere else.

You can’t fix that with a transformation programme that reports progress for eighteen months, then quietly stalls. You fix it by becoming the kind of organisation that doesn’t need transformation programmes.

The feature gap closed. The velocity gap hasn’t.

We’re measuring what separates high-performing banks from the rest: how quickly they spot friction, test fixes, and deploy improvements that customers feel. Our upcoming Top UK Banks Digital Maturity Report 2026 benchmarks CX velocity across the industry—tracking who’s improving continuously and who’s quietly stalling.

Click here to download the report now

If you’re working on closing the velocity gap at your organisation or want to discuss how to build the kind of capability that doesn’t need transformation programmes, get in touch.

The post The feature gap has closed. So why are customers still leaving? appeared first on Remarkable.

UK challenger banks have won. But is it the battle, or the war?

Monzo achieved its first full-year profit in March 2024. Starling has been profitable for four consecutive years, and Revolut recorded a £1.5 billion profit last year. So, the model is proven to work.

But profitability creates problems of its own. And the forces that made incumbents such easy targets are starting to slow the challengers down, too.

The victory that changed the rules

For almost a decade, the pitch was simple. Challengers move fast. Incumbents drag behind, weighed down by legacy tech and regulatory burden. That pitch struck a chord with the market.

We know why traditional banking was so easily disrupted. Ring-fencing alone cost billions to implement. And half of IT budgets went to compliance rather than innovation, so the Big Four lost market share as a result.

But the same profitability that proved the challenger model also ended the conditions that made it possible. 

When you’ve got nothing to protect, you can experiment freely. When you’ve got margin to defend, every experiment is that bit riskier. Customers rightly always expect stability. Regulators expect compliance at scale. And boards want to know the return before you ship.

How many startups have founders who stay close to the work? Who are present in every room? Involved in the code and the copy? And how many, once they hit profitability, get nudged toward stepping back? Toward delegating? Toward treating departments as black boxes?

The first approach builds things. The second protects things.

Monzo has 12 million customers. Except it doesn’t.

In June 2025, Monzo disclosed that 33% of its customers use it as their primary bank. Which means 8 million people completed onboarding, passed KYC, received a card, and then…didn’t really show up. They’re on the books, and they require compliance. But they generate minimal revenue.

The FCA’s strategic review found that only 25% of digital challenger accounts function as main accounts, compared to 55% across the broader market. Three-quarters of those headline customer numbers are secondary accounts, dormant accounts, or people who opened an account out of curiosity and never came back. 

Starling is more transparent than most. Its 2025 annual report states that 79% of core accounts are active. That’s better than the industry standard, but it still means there are around one million accounts that are idle and require regulatory oversight. 

Revolut’s average consumer deposit is £575. Starling’s is £2,600. That gap tells you something about the depth of those customer relationships. The challengers are carrying the cost of twelve million customers while generating revenue from four million.

And those eight million disengaged customers aren’t loyal or locked in. They’re sitting there waiting for someone to give them a reason to move.

What happened to the founders

Anne Boden founded Starling, built its culture, and led it to profitability in 2022. In July of that year, she explained that Starling had grown from an aspiring challenger to an established bank, and the role of CEO and major shareholder “ultimately differ and require distinct approaches.” She stepped down as CEO in September 2023. By 2024, she’d left the board entirely.

Predictably, changes came quickly. Starling’s new CEO rolled out a compulsory return-to-office policy, which, to be fair, was in step with the wider industry. For Starling, though, it was also an external signal of the transition. One employee summed it up on record: “Starling has lost its unique culture. It’s no longer a startup. It’s a traditional bank.”

Monzo’s story is different, but the lesson’s the same. The CEO departed over reported disagreements about IPO timing. The underlying conflict seems to have been about the strategy appropriate for a profitable company. Internal sentiment suggested that the bank was suffering from growing pains, with one team member stating that “Monzo has increasingly felt more like a traditional bank. Compliance plays a significant role in every aspect.”

Compliance. 

There it is again.

The velocity problem

Every dimension of scale slows you down that little bit more.

Monzo grew from 30 employees to over 2,000. Starling went from 60 to more than 3,000. Product lines grew to match, with current accounts, savings, loans, investments, mortgages, business banking and international transfers on offer. Each product has dependencies. Each change introduces administration, technology and compliance, but on systems that didn’t exist five years ago.

The velocity problem is illustrated best by product releases. All three banks shipped current accounts within two to four years of founding, and business banking took four to five years. But tertiary products show the issue. Starling is nine years old and still hasn’t launched lending or investment products.

There’s a subtler signal, too. Revolut announced mortgages for H1 2025, but the Irish launch has now slipped to 2026, twelve months overdue. Monzo used to publish detailed release notes for every app version. They stopped after 2018. When velocity was a competitive advantage, they shouted about it.

Now they don’t mention it. 

Why would they?

Teams that once built features now build compliance systems, resilience plans, and regulatory reports. Early products shipped quickly. Later products stalled. Or never arrived.

Compliance catches up in the end

Regulatory burden used to be an incumbent problem. Not anymore. 

The FCA fined Monzo £21 million for AML failures. The firm had “onboarded customers on the basis of limited, and in some cases, obviously implausible information.” Starling was fined £29 million for “shockingly lax” financial sanctions screening.

Both banks had operated under Voluntary Requirements for years before these fines, restricting their ability to onboard high-risk customers for this very reason. 

The hiring data tells the same story. In 2026, compliance and risk roles account for more than half of all banking vacancies in UK fintech, up from roughly 20-25% historically. The pattern has held for three consecutive years, suggesting a structural shift in how these companies allocate resources.

And the FCA’s December 2025 review made the position clear: “We remain of the view that there are limited differences in the inherent financial crime risks faced by challenger banks, compared with traditional retail banks.”

In other words, the challengers are now saddled with the same restrictions as everyone else, and the teenage years, when these can be treated fairly laxly, are over. 

Where the threat comes from 

Nobody is building “the new Monzo” to attack Monzo’s retail position. The threat is more nuanced, with specialists targeting specific customer segments rather than competing across the board. 

SumUp has 4 million merchants and €1 billion in customer deposits. They’re applying for banking licences in the EU and UK with explicit plans to move into SME banking. Using payments data that challengers don’t have. 

Challengers won broad markets with better tech and better experience. Now specialists are attacking the profitable niches with sharper tools and tighter focus. 

And the challengers’ response, so far, has been to defend margin rather than defend territory. 

That’s the pattern. That’s what settling down looks like.

How do you innovate at scale? 

According to O’Reilly and Tushman, companies that run innovation and operations as separate units achieve breakthrough innovation more than 90% of the time. Those using traditional structures manage it about a quarter of the time. 

Banks keep trying it…and it keeps failing. 

Goldman Sachs built Marcus as a structurally separate digital bank. It had different leadership and a different ‘fresh’ culture, and it was kept away from the investment banking core. By 2021, it had $100 billion in deposits and 14 million customers. But by 2023, it had accumulated $3 billion in losses, cycled through three leaders, and begun selling off the assets. Similarly, ING launched Yolt with genuine independence and a head start on open banking, but it shut down after failing to reach scale. 

There’s a clear pattern here. Separate innovation units in banking produce either spectacular losses or impressive-sounding programmes that never really see the light of day. 

What works is full transformation. DBS didn’t build a lab and hide its team away. It restructured the entire organisation around 33 platforms, each with joint business-technology leadership. Innovation was measured against cost-to-income ratio and customer satisfaction – proper metrics that demonstrate impact. And Euromoney named it World’s Best Digital Bank three times. 

But DBS was an incumbent. It had to learn transformation from scratch. Challengers don’t because they started ‘transformed’. That was the whole point. They were born in the end state that traditional banks can’t reach. 

The danger now is to respond to scale by copying the incumbent playbook and protecting the margin, while hoping a separate team will figure out the future. That approach has a consistent track record in banking, and it’s not a great one. 

Challengers have something incumbents never will – they’ve seen the digital utopia, and they’ve transformed an industry. That muscle memory exists somewhere. The question is whether they can do it again at scale, while managing compliance burdens, board expectations, and margin protection.  

The banks that thrive over the next five years will be the ones that find a way to move fast again. Not by ignoring compliance. But by refusing to let it become an excuse for standing still. 

That’s harder than it sounds. 

But not standing still was exactly why the challengers succeeded in the first place. 

The challengers’ proved transformation is possible. What comes next? 

We’re tracking how UK banks—challenger and incumbent alike—are navigating the tension between innovation velocity and operational scale. Our upcoming Top UK Banks Digital Maturity Report 2026 benchmarks where the industry stands today: which banks are still moving fast, which have settled, and what separates the two. 

Pre-register to download the report

Want to discuss what digital maturity looks like at scale, or how to maintain innovation momentum while managing compliance and growth? Get in touch—we’d love to hear your perspective.

The post How do challenger banks resist the urge to settle down? appeared first on Remarkable.

For many digital, marketing, and product teams, experimentation remains one of the most powerful yet misunderstood levers for growth. Not because the capability is flawed, but because the story around experimentation is often told in a way that fails to resonate with senior leadership. 

Executives speak in the language of risk, capital, and strategic clarity. Experimentation teams often speak in tests, lifts, and variants. Those words rarely connect, and that disconnect stops organisations from unlocking the full value of Optimizely. 

Teams frequently struggle to secure budget, sponsorship, or long-term investment in experimentation because their reporting and narrative are too focused on what was tested rather than what was decided. 

Executives aren’t looking for: 

• A summary of variants 

• A breakdown of traffic splits 

• A list of statistical outcomes 

This is why reframing experimentation is essential, not as tactical optimisation, but as an enterprise decisioning capability. 

Reframing Experimentation as a Leadership Asset

When positioned correctly, experimentation becomes a strategic advantage that supports the core responsibilities of the C-suite.

1. Risk Management

Optimizely reduces uncertainty by validating decisions before they scale. Instead of gambling on redesigns, campaigns, or new features, leaders can replace assumption-driven moves with evidence-backed confidence.

2. Capital Efficiency

Every investment, whether design, media, or development, is scrutinised for return. Experimentation ensures investment is deployed where it produces measurable value, not where it “feels right”.

3. Strategic Optionality

C-Suite often need the ability to pivot. Optimizely enables organisations to test strategic pathways in small, safe increments before committing fully, preserving optionality while still progressing. 

This reframing is what enterprise CMOs and CTOs care about most: growth, resilience, and a high-performing digital experience backed by data and strong platform engineering.

Reporting What Actually Matters

To gain credibility, teams must shift from test-centric to decision-centric storytelling. 

Instead of: 

“We ran a button colour test. Variant B won.” 

Tell the story like this: 

• Business Problem
  “Checkout abandonment was limiting revenue in key markets.” 

• Decision Enabled
  “We validated a new checkout pattern that improves clarity and reduces user friction.” 

• Financial or Strategic Impact
  “This unlocks an expected multimillion revenue uplift annually with no additional media spend.” 

This is the type of outcome-driven reporting that aligns perfectly with how enterprise leaders evaluate performance, an approach consistent with Remarkable’s focus on ROI, measurable impact, and data-driven optimisation across digital experiences.  

Why This Matters Now 

Enterprise leaders are under pressure to: 

• Prove ROI 

• Hit revenue targets 

• Improve customer experience 

• Deliver faster with fewer resources 

• Adopt AI  

Experimentation sits at the centre of all of these. 

Your ability to speak the language of leadership determines whether experimentation stays a niche practice, or becomes a strategic engine that shapes the organisation’s growth agenda. 

The post Speaking the Language of Leadership with Optimizely Experimentation appeared first on Remarkable.

Most experimentation programmes don’t fail because the tests are wrong. They fail because the learnings disappear.

The post Turning Optimizely Insights into Organisational Learning appeared first on Remarkable.

As organisations scale their experimentation practice, the challenge is no longer “Can we run experiments?” It becomes: Can we learn fast enough, synthesise effectively enough, and maintain strategic focus across dozens or hundreds of tests? 

This is precisely where Optimizely Opal AI becomes transformative. 

Why Opal is Different

Opal is not a chatbot. It is Optimizely’s AI-native agent orchestration platform, designed to analyse data, surface insights, coordinate workflows, and execute multistep processes across the marketing and experimentation lifecycle.  

Modern experimentation programmes generate enormous volumes of data, event logs, learnings, audience signals, hypotheses, content variations. Teams quickly become overloaded. 

Opal addresses this head-on by providing: 

• Context aware intelligence, enriched with brand-specific data, performance history, and compliance rules.  

• Multiagent workflows, enabling experimentation tasks to be chained, automated, and executed without manual coordination.  

• Natural language orchestration, turning human intent into structured, scalable activity.  

This shifts experimentation from a labour-heavy practice into a strategic, AI-augmented operating system. 

Teams traditionally spend large amounts of time digging through analytics dashboards, past experiment reports, and content archives. Opal changes this by acting as an intelligence layer across your experimentation ecosystem: 

• Surfacing patterns in historical experiments 

• Summarising results and insights at scale 

• Understanding brand context and compliance as it analyses data

How to Succeed with Opal

One of the most common failure modes in experimentation is duplication: teams unknowingly rerun similar tests, reinvent hypotheses, or lose sight of what has been learned. Opal helps mitigate this by acting as a searchable, intelligent memory system. 

From your internal materials: 

• Opal can analyse past tests, suggest new content or audience ideas, and automatically create experiments with appropriate audiences, variants, and traffic allocation.  

• It can generate tone-specific content variants, ideal for rapid hypothesis development or experiment ideation.  

At scale, experimentation requires thinking beyond individual tests. You need visibility into: 

• Over-tested pages or journeys 

• Underexplored opportunities 

• Imbalance between incremental optimisation and innovation bets 

• Areas where insights are not being operationalised 

Experimentation leaders who adopt Opal early are able to scale the impact of their programmes without expanding team size, while building a durable institutional memory that accelerates learning across the organisation. By eliminating duplicated tests and elevating the quality of hypotheses, Opal helps teams unlock experimentation across more journeys and functions, all while strengthening alignment between experimentation, content, and product disciplines. Most importantly, it reduces the time between insight discovery and action, allowing organisations to move faster and with greater confidence. In this way, Opal becomes the connective tissue linking experimentation to the wider digital experience ecosystem. 

The post Scaling Experimentation Strategy with Opal AI appeared first on Remarkable.

When experimentation runs without a North Star, a single, unifying measure of success, it quickly devolves into disconnected tests, unclear priorities, and “optimise-for-the-sake-of-optimising.” The result? Lots of activity, very little impact. 

A North Star metric transforms experimentation from a tactical activity into a strategic engine. Without it, even the most sophisticated experimentation platform becomes a scattergun of ideas, rather than a disciplined system for accelerated learning.

What makes a strong experimentation North Star?

• Customer-centric – It must reflect value as the customer experiences it, not internal vanity measures. 

• Leading, not lagging – Revenue is important, but it lags. Great North Stars are ambassadors for revenue acceleration. 

• Sensitive to experimentation – Teams need to be able to influence it through tests. If experiments can’t move it, it’s not a North Star. 

Common examples include: 

• Task completion rate  

• Activated users  

• Revenue per active user  

These metrics are close to behaviour, close to value, and highly experiment-responsive. 

A North Star is only powerful when it shapes how experiments are designed, run, and interpreted. It forces teams to think beyond isolated test outcomes and to consider how a change influences the broader user journey.

Break the North Star into its controllable components. 

For example:
If your North Star is revenue per user, your decomposed submetrics might be: 

• Product Page Engagement  

• Add to Basket Completion  

• Product Page Views  

• Basket Page Views  

• Checkout Form Completion 

Not all uplifts are created equal

The difference between good experimentation programmes and great ones is simple: 

Good programmes deliver small wins, great programmes deliver organisational learning.

OMVP-level practitioners help organisations evolve from optimisation to directional transformation, using experimentation to validate strategic leaps, not just microinteractions. 

With a well defined North Star experimentation comes: 

• A source of truth for product and CX direction 

• A multiplier for design and content investment 

• A shared language across marketing, product, and engineering 

• A way to de-risk innovation while accelerating momentum 

Optimizely provides the infrastructure for experimentation, analytics, feature rollouts, and behavioural insight, but the North Star provides the purpose. 

The post Designing an Experimentation North Star with Optimizely appeared first on Remarkable.

As the year ended, Remarkable’s Client & Sales team looked ahead to 2026, sharing their boldest predictions for the future of digital, sales, and marketing.

This year promises to be transformative, with AI moving from experimental to essential in nearly every business process. Companies that adapt quickly will gain a competitive edge, while those that hesitate risk falling behind.

Here’s what the team see on the horizon.

Visual Search Becomes the Primary Retail Channel

Ian MacArthur sees visual search overtaking text queries in retail, with “camera-first” searching becoming the norm for fashion, home décor, and more. This shift will redefine how consumers interact with brands, making product discovery faster and more intuitive. Retailers will need to optimise their catalogues for visual recognition and invest in AI-driven image search capabilities to stay relevant.

Everyone Will Need to Be “More Developer”

Alex Lee believes that everyone will need to become “more developer”, learning to use code and APIs to automate and innovate. This trend reflects the growing demand for technical literacy across all roles, not just engineering. Businesses will likely offer training programmes and low-code platforms to empower employees.

Content Strategy: The AI Advantage of 2026

Steph Powis highlights content strategy as the ultimate competitive edge, with brands needing to create clear, authoritative content trusted by both humans and AI. High-quality content will influence search rankings and AI-driven recommendations, making it a cornerstone of marketing success. Companies that fail to prioritise content integrity risk losing visibility and credibility in an AI-dominated ecosystem.

Advertising Revenue Moves to AI Platforms

John Whittome expects advertising revenue to shift to AI platforms, with conversational ad formats, context-driven placements, and transaction-based models. This evolution will blur the lines between advertising and customer engagement, creating more personalised experiences. Brands will need to rethink their ad strategies, focusing on relevance and real-time interaction to maximise ROI.

Cyber Security Remains Critical

Marie Heinsen warns that cyber security will remain critical, especially as data visibility to LLMs increases. With AI systems accessing vast amounts of sensitive information, the risk of breaches will grow exponentially. Organisations must invest in robust security frameworks and continuous monitoring to safeguard trust and compliance.

AISoV: The Metric of the Year

Kier Humphreys tips AISoV (AI Share of Voice) as the metric of the year, though it will remain difficult to quantify—making attribution and data even more valuable. Measuring influence in AI-driven channels will become a priority for marketers seeking to understand brand impact. Expect new tools and methodologies to emerge, aiming to capture this critical metric.

Building Trust

Emma Nijjar emphasises the importance of building trust through transparency and genuine human connection. In a world dominated by automation, authenticity will set brands apart. Companies that prioritise ethical practices and clear, human communication will foster loyalty and long-term relationships.

Human is Still Important

Like Emma, Kartika Chandramohan predicts that as AI adoption rises, clients will value unique, human-created ideas as the new premium. Creativity and emotional intelligence will remain irreplaceable, offering differentiation in an increasingly automated market. Businesses should invest in nurturing these human skills alongside technological innovation.

Agentic AI Applications

Peter Clisby foresees the rise of Agentic AI applications—built by developers, integrating business logic and leveraging both LLMs and classic AI services. These applications will enable autonomous decision-making, streamlining workflows and reducing operational overhead. Companies that embrace this model will unlock new efficiencies and competitive advantages.

The Rise of SLMs (Small Language Models)

Paul Stephen expects brands to shift towards SLMs (Small Language Models) to retain control over their data and IP. These models offer greater customisation and privacy, addressing growing concerns around data governance. Organisations will increasingly balance scalability with security, opting for tailored AI solutions.

A Scare in the Market

James Gray predicts a big AI market scare at some point in H1 of 2026, and a ‘severe correction’ when AI investors have a “show me the money” moment. This shake-up will likely separate hype from reality, forcing companies to demonstrate tangible ROI. Businesses that have built sustainable AI strategies will weather the storm, while speculative ventures may struggle.

Three Trends for 2026

Ross Breen identifies three key trends: conversational interfaces becoming standard, personalisation as a baseline expectation, and trust as the defining differentiator in an AI-driven world. These shifts will reshape customer experiences, making adaptability and transparency essential, and brands that align with these trends will thrive.

In summary:

2026 will be a year of reckoning for AI, where those who blend technology with human creativity and trust will lead the way. The winners will be those who innovate responsibly, balancing automation with authenticity.

What lies ahead for your business this year?

The post Remarkable’s Staff Predictions for 2026: The Year AI Grows Up appeared first on Remarkable.

With the launch of SitecoreAI at Sitecore Symposium in November, Sitecore is reshaping how marketers create, manage, and optimise digital experiences.

Whether you were already using Sitecore XM Cloud, or considering migrating from XP or even another DXP, understanding what SitecoreAI brings to the table is essential.

From built-in experimentation tools to the new Agentic Studio, SitecoreAI empowers teams to work smarter, faster, and more creatively.

Below are the five things that every marketer should know about SitecoreAI, and why they matter.

1. Free upgraded personalisation and A/B testing out-of-the-box

One of the biggest hurdles for brands adopting personalisation and experimentation has traditionally been cost and complexity. SitecoreAI eliminates both.

SitecoreAI includes upgraded personalisation and A/B testing tools compared to the basic features offered out-of-the-box in XM Cloud with a free basic tier of what was previously Sitecore Personalize embedded in the platform and available immediately. This means that:

• You can spin up your first personalisation rules without additional licensing. 

• A/B tests can be launched directly within your content workflow. 

• Teams can start optimising from day one. Now there are no excuses not to get started.

For marketers, this lowers the barrier to data-driven decision-making and encourages a culture of continual improvement.

2. Agents and Flows automate content, SEO, and much more

SitecoreAI introduces Agents and Agent Flows, AI-driven helpers designed to automate common marketing and content tasks. 

With over twenty pre-built Agents available to use in the Agentic Studio library from Day One, teams can start automating immediately. These Agents can support tasks such as: 

• Producing structured content 

• Optimising SEO metadata 

• Translation 

• Competitor analysis 

• Brief generation 

Flows allow you to combine Agents into automated multitasking workflows using drag-and-drop tools. The result is faster production, less manual effort, and more time for strategic thinking.

3. Build a Brand Kit so the AI knows your brand inside out

To ensure consistent, on-brand output, SitecoreAI includes a Brand Kit which acts as your central hub for defining brand rules that the AI will follow. Within your Brand Kit, you can define: 

• Tone of voice 

• Brand vocabulary and messaging 

• Visual guidelines including logos, colours, imagery preferences 

• Product information 

• Example content for reference 

• Previous campaigns 

This means that every piece of content that the AI features help generate, from headlines to hero copy, feels aligned with your brand identity. It dramatically reduces revision time and protects brand integrity at scale.

4. All tools are tightly integrated under one roof

One of the standout advantages of SitecoreAI is that the disparate tools aren’t bolted on, everything is deeply integrated into a single ecosystem. This tighter integration delivers: 

• Unified workflows across content creation, personalisation, analytics, and optimisation 

• Consistent interfaces that are easier for teams to adopt 

• Fewer integrations, configuration, and set-up 

• Smarter AI outputs because the system understands context across your tools 

In short, features work seamlessly within the SitecoreAI platform because it’s designed to be a single integrated platform, rather than a set of individual tools connected together. As Sitecore says, it is “composed, not composable”.

5. There’s no extra charge for AI features

Perhaps the most surprising thing about SitecoreAI is that the AI features come at no extra cost to XM Cloud customers. 

This removes a major barrier to entry. You don’t need separate AI licenses, credits, or subscriptions. Every customer can immediately: 

• Generate content with AI 

• Automate tasks with Agents & Flows 

• Run personalisation and A/B tests 

• Apply Brand Kit rules 

• Use AI-assisted enhancements across the platform 

For marketers, this means you can leverage AI to its fullest without worrying about hidden costs. 

Final thoughts

SitecoreAI is more than a collection of features: it’s a strategic shift that helps marketers work more efficiently, elevate customer experiences, and scale personalisation without the heavy lifting. 

By lowering barriers to testing, automating repetitive tasks, and providing deeply integrated AI support, Sitecore is making enterprise-grade experience optimisation more accessible than ever. 

The post 5 Things Every Marketer Needs to Know About SitecoreAI appeared first on Remarkable.