Data and Business Intelligence Services UK & UAE — Vistoplex

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Data Practice — UK & UAE

Data & Business Intelligence for Smarter Decisions.

We help businesses of all sizes turn their data into decisions. From data strategy and analytics platforms to executive dashboards, CRM integration, predictive analytics, and GDPR compliance — we build the data infrastructure that makes your business measurably smarter.

Data Strategy Analytics Platforms Executive Dashboards Predictive Analytics GDPR Compliance UK & UAE
Data sources mapped & audited
GDPR status assessed
Audit from £2,000
Markets GB · AE
The core problem

Most businesses are data rich
and insight poor.

Invisible operational bottlenecksData would make them visible — but it sits in disconnected systems.
Intuition-based pricing decisionsMade without the margin data that could inform them.
Marketing spend without attributionNo visibility of which channels produce retained customers.
Manual reporting consuming staff timeHalf-day compilation exercises for data that should be live.

Ask almost any business leader whether their organisation collects data and the answer is yes — often enthusiastically so. Ask them whether they can see, in a single view, how their business is performing right now, why it is performing that way, and what is most likely to happen next — and the answer is almost invariably no.

The gap between those two positions is not a data shortage problem. Most mid-sized businesses have more data than they know what to do with — spread across a CRM, an accounting system, a website analytics platform, a marketing automation tool, and a collection of spreadsheets that someone maintains manually because the systems do not talk to each other. The problem is not the quantity of data. It is the absence of a coherent architecture that brings it together.

Data is only valuable when it is trusted, accessible, and connected to the decisions that matter.

The commercial cost of this gap compounds quietly. Pricing decisions are made on intuition rather than margin data. Customer acquisition spend is allocated without visibility of which channels actually produce retained customers. Operational bottlenecks that data would make visible remain invisible. The organisation continues to collect data that it has no effective mechanism to use.

Vistoplex builds the data infrastructure that closes this gap — for businesses at every stage, from growing SMEs building their first coherent customer data view to enterprise organisations requiring a multi-system analytics platform with predictive modelling capability.

Our data services

Six disciplines.
One audit.

Every engagement begins with a data audit. Whether you need a single service or a full data intelligence programme, the audit gives you and us the accurate picture that makes everything that follows work correctly.

Data strategy & architecture · Analytics platform implementation · Executive & operational dashboards · Customer data strategy & CRM integration · Predictive analytics & forecasting · GDPR & data compliance. All audit-led. All fixed-entry-point pricing.
01 / DATA STRATEGY
Data Strategy & Architecture
A data strategy is a documented plan defining how an organisation will collect, store, manage, govern, and use its data. Data architecture is the technical design of the systems and standards that implement that strategy. Most organisations that struggle to use their data effectively lack not the data itself but a coherent strategy governing it.
Data strategy is where most data initiatives should begin — and where most do not. The typical pattern is technology-first: a business purchases an analytics tool, then discovers the tool cannot produce the insights they expected because the underlying data is fragmented. The tool is blamed for a failure that the absence of a strategy made inevitable. A coherent data strategy begins with the decisions the business needs to make, then works backwards to define what data is required and what architecture is needed.
Data audit entry point: from £4,999 · Produces current-state assessment and strategy recommendations
What this service covers
Current-state data assessment — mapping existing data sources, systems, flows, and gaps
Data requirements definition — identifying what data is needed to support key decisions
Architecture design — defining the target data architecture including storage, integration, and access
Data governance framework — standards for data quality, ownership, and maintenance
Technology selection — evaluating and recommending the right tools for the architecture
Implementation roadmap — a phased plan for moving from current state to target architecture
Data literacy assessment — understanding current capability and what development is required
02 / ANALYTICS PLATFORMS
Analytics Platform Implementation
An analytics platform collects, processes, and presents business data in a format that supports decision-making — typically combining data from multiple source systems into a unified view. Platforms include Power BI, Tableau, Looker, Google Looker Studio, and Qlik. We are platform-agnostic: we recommend the tool that fits the organisation's environment, not the tool we have a commercial relationship with.
We approach analytics platform implementation from the user back. Before any platform is selected, we establish what specific views of the business data each user group needs — what questions they are trying to answer, what decisions they are trying to make. Platform selection follows from that understanding. For most small businesses, Google Looker Studio provides an accessible starting point. For mid-market organisations, Power BI or Tableau typically provides the right balance. For enterprise environments with sophisticated data engineering requirements, Looker or Qlik may be more appropriate.
Data audit entry point: from £4,999 · Includes platform recommendation and implementation scoping
What this service covers
Platform evaluation and selection — assessing the right tool against specific requirements
Data source connection — integrating with CRM, ERP, marketing platforms, website analytics, financial systems
Data model design — structuring data within the platform to support required reports
Report and dashboard development — building the specific views required by each user group
User training and adoption support — ensuring users can access and act on data independently
Maintenance and optimisation — ongoing data source management and performance tuning
03 / DASHBOARDS
Executive & Operational Dashboards
An executive dashboard presents key business performance metrics to senior leadership for strategic decision-making — combining financial performance, operational efficiency, customer metrics, and market indicators. An operational dashboard presents real-time data to operational managers covering the specific metrics relevant to day-to-day performance. Both require careful design to present the right data to the right audience.
The most common failure mode of business dashboards is not technical — it is design. A dashboard that presents every available metric to every user produces cognitive overload rather than clarity. The discipline of dashboard design is the discipline of deciding what to exclude. We design dashboards with the specific decision-making context of each audience as the governing constraint. A board member reviewing monthly performance needs different visibility from an operations manager monitoring real-time throughput.
Data audit entry point: from £4,999 · Includes KPI workshop and dashboard specification
What this service covers
Audience and decision-context analysis — establishing what each user group needs to see and why
KPI definition and metric prioritisation — identifying genuinely diagnostic measures for each audience
Data source mapping — establishing which source systems contain the required data
Visual design — dashboard layout, visual hierarchy, colour coding, and interaction design
Development and data connection — building the dashboard and connecting to live data sources
Testing and validation — confirming data accuracy against source systems before deployment
User training and ongoing maintenance — ensuring adoption and keeping data sources current
04 / CRM & CUSTOMER DATA
Customer Data Strategy & CRM Integration
A customer data strategy defines how an organisation collects, stores, manages, and uses data about its customers across all touchpoints. CRM integration connects a CRM platform to the other systems that generate and use customer data — website, marketing automation, e-commerce, support, and financial systems — to create a unified customer record reflecting the full history of each customer relationship.
Customer data is the most commercially valuable data most businesses collect — and the most commonly mismanaged. The typical situation is one where customer information exists in multiple places simultaneously: contact details in the CRM, purchase history in the e-commerce platform, support history in the helpdesk, marketing engagement in the email platform. No single system contains a complete picture. No one can see, at a glance, the full context of their relationship with a specific customer — their history, their value, their engagement.
Data audit entry point: from £4,999 · Includes customer data mapping and CRM recommendation
What this service covers
Customer data audit — mapping existing customer data across all systems, identifying gaps and duplicates
CRM platform evaluation and selection — recommending the right CRM for size, complexity, and budget
CRM implementation or optimisation — configuring to support specific sales, marketing, and service processes
System integration — connecting the CRM to website, marketing, e-commerce, support, and financial systems
Data migration — moving historical customer data from legacy systems cleanly and accurately
Customer segmentation design — the framework enabling targeted marketing and personalised service
Ongoing data quality management — processes and tooling to maintain data accuracy over time
05 / PREDICTIVE ANALYTICS
Predictive Analytics & Forecasting
Predictive analytics applies statistical modelling and machine learning to historical data to forecast future outcomes — such as customer churn probability, sales demand forecasting, inventory optimisation, or risk scoring. For businesses with sufficient historical data, predictive models replace intuition-based forecasts with evidence-based probability estimates, improving the quality of planning and operational decisions.
Predictive analytics sits at the intersection of data engineering, statistical modelling, and business domain understanding — which is why it is so commonly delivered poorly. A model that is technically sophisticated but built on the wrong question delivers no commercial value. Our approach begins with the decision — what specific choice does this organisation make repeatedly, where better information about the likely outcome would improve the quality of that choice? Our team has direct experience of forecasting tool development in retail environments, building systems that informed daily purchasing decisions for large commercial teams.
Data audit entry point: from £4,999 · Includes data readiness assessment and model feasibility review
What this service covers
Problem definition — establishing the specific decision the model will inform and its commercial value
Data readiness assessment — evaluating whether available historical data is sufficient in volume and quality
Model design and selection — choosing the appropriate modelling approach for the specific prediction problem
Model development and validation — building and testing against held-out historical data
Output design — presenting model outputs in a format operational users can act on without statistical expertise
Integration — embedding model outputs into the operational systems where decisions are made
Monitoring and recalibration — tracking model performance and recalibrating as conditions change
06 / GDPR & COMPLIANCE
GDPR & Data Compliance
GDPR governs how organisations in the UK and EU collect, store, process, and use personal data. UK organisations are subject to the UK GDPR and the Data Protection Act 2018. Non-compliance carries penalties of up to £17.5 million or 4% of global annual turnover. Most small and medium-sized businesses are less compliant than they believe — the gap between having a privacy policy and meeting the full range of GDPR obligations is significant.
GDPR compliance is not a one-time exercise — it is an ongoing operational discipline. The practical obligations that most businesses underestimate include: maintaining an accurate record of processing activities (Article 30), conducting Data Protection Impact Assessments for high-risk processing (Article 35), managing data subject rights requests within statutory timeframes (Articles 15–22), and managing contractual obligations with third-party processors. For businesses operating in the UAE, the UAE Personal Data Protection Law introduces equivalent obligations — our multilingual capability positions us to address compliance requirements in both jurisdictions simultaneously.
Data audit entry point: from £4,999 · Includes GDPR compliance gap assessment and remediation priority report
What this service covers
GDPR compliance audit — structured assessment of current data processing practices against UK GDPR requirements
Gap analysis and remediation plan — prioritised compliance gaps with specific remediation actions
Article 30 record of processing activities — developing and maintaining required documentation
Privacy notice development — drafting GDPR-compliant privacy notices for websites and applications
Consent management — designing mechanisms that meet GDPR standards
Data subject rights procedures — processes for handling access, deletion, and portability requests
UAE PDPL compliance — equivalent assessment and remediation for businesses operating in the UAE
Ongoing compliance monitoring — quarterly reviews maintaining currency of compliance documentation
Start here

Start with a
data audit.

A data audit is a structured assessment of an organisation's current data environment — covering what data exists, where it is stored, how it flows between systems, how it is governed for quality and consistency, what compliance obligations it creates, and what analytical value it could generate if properly structured.

Most clients find the audit surfaces at least one significant compliance risk, one data quality issue affecting operational performance, and one analytical opportunity they had not previously identified.

Every data and business intelligence engagement we undertake begins with an audit — and for good reason. The most common cause of failed data initiatives is a solution designed without adequate understanding of the data it is supposed to work with. Analytics platforms built on fragmented, inconsistent source data produce fragmented, inconsistent outputs.

All audit outputs belong to your organisation regardless of whether you proceed to a further engagement.

Audit pricing tiers
Standard data audit
Up to 5 data sources
From £2,000
Most common for SMEs
Comprehensive data audit
5–15 data sources
From £3,500
Enterprise data audit
15+ sources, multi-territory
From £6,500
GDPR compliance audit
Standalone regulatory assessment
From £2,500
Standalone option
What the audit covers
Step 01
Data Source Mapping
We identify and document all data sources within the organisation — every system that generates, stores, or processes data relevant to the business — and map the flows between them.
Step 02
Data Quality Assessment
We assess the quality of data in each source: completeness, accuracy, consistency, timeliness, and the specific quality issues affecting the organisation's ability to use its data effectively.
Step 03
GDPR Compliance Assessment
We assess current data practices against UK GDPR requirements — identifying gaps, risks, and the specific remediation actions required to achieve compliance.
Step 04
Analytical Opportunity Identification
We identify the specific analytical capabilities that the organisation's existing data could support — the questions that could be answered and the commercial value those improvements represent.
Step 05 · Output
Written Findings Report
Data source inventory and flow diagram · Data quality assessment by source · GDPR compliance gap assessment · Analytical opportunity map · Prioritised recommendations register ordered by commercial impact. Belongs to your organisation regardless of whether you proceed.
Every stage of business

Data intelligence for
every size of organisation.

The approach differs between a growing SME building its first coherent customer data view and an enterprise organisation requiring a multi-system analytics platform. The underlying principle is the same — data is only valuable when it is trusted, accessible, and connected to decisions.

For Growing SMEs
Foundation first.
Get the basics right.
Your data challenge is typically one of foundation — getting the basics right before attempting anything more sophisticated. The priority is usually a coherent customer record, a reporting dashboard that gives you visibility of the metrics that actually matter, and GDPR compliance that is genuine rather than a privacy policy that nobody maintains.
  • A focused data audit — typically 2 to 5 data sources — that identifies the specific gaps and opportunities in your current environment
  • A CRM integration that consolidates customer data from your website, marketing tool, and sales pipeline into a single coherent view
  • A simple executive dashboard — revenue, pipeline, customer health — that gives you a daily view without IT involvement
  • A GDPR gap assessment that tells you honestly where you stand and what needs to change
SME
For Mid-Market & Enterprise
Coherence at scale.
One architecture.
Your data challenge is typically one of coherence — bringing together a complex multi-system data environment into an architecture that produces reliable, accessible, and trustworthy information for the people who need it. The priority is usually a data strategy that governs the whole environment rather than adding another tool that addresses a symptom without treating the cause.
  • A comprehensive data audit across 5 to 15 data sources — producing the accurate current-state assessment that makes subsequent initiatives work correctly
  • A data strategy and architecture that governs the whole environment rather than treating symptoms individually
  • An analytics platform that actually gets used — designed from the user back, not from the technology forward
  • Predictive capability that improves the quality of material operational or commercial decisions
  • A compliance posture that is genuinely defensible — including UAE PDPL for businesses operating across both markets
ENT
Measurable outcomes

Data intelligence results
from real organisations.

Four case studies across all six service areas — with the specific numbers that demonstrate commercial impact in practice.

Executive Dashboard · UK Professional Services
Dashboard eliminates half-day monthly report compilation — deployed in 6 weeks.
A UK professional services firm with 85 employees had no consolidated view of business performance — financial data in Xero, project data in a project management tool, client data in a CRM, no integration between them. A data audit identified three integrations required to consolidate these sources. An executive dashboard was built and deployed in six weeks, giving the leadership team a daily view of revenue, utilisation, pipeline, and client health.
6wk
Audit to live dashboard
0.5d
Reporting time saved monthly
3
Integrations built
CRM Integration · Dubai Retail
12,000 customer records consolidated — £38,000 email revenue in 90 days.
A Dubai-based retail business with 12,000 customer records spread across three disconnected systems — a POS, an e-commerce platform, and a marketing tool — commissioned a customer data audit and CRM integration programme. The programme consolidated all records into a single CRM, deduplicated 2,800 duplicate records, and built the segmentation framework that enabled the first targeted email campaigns the business had been able to run.
12k
Records consolidated
2,800
Duplicates removed
£38k
Email revenue · 90 days
Predictive Analytics · UK Retail
Demand forecasting model reduces forecast error by 34% in 6 months.
A UK retail organisation was experiencing significant forecasting inaccuracy — over-ordering in some categories and stock-outs in others — at material cost to margin and customer satisfaction. A demand forecasting model built on three years of sales history, incorporating seasonality, promotional effects, and supplier lead times, reduced forecast error by 34% within the first six months — directly reducing over-stock write-downs and improving in-stock rates.
34%
Forecast error reduction
3yr
Sales history used
6mo
To measurable result
GDPR Compliance · London HealthTech
Seven compliance gaps remediated ahead of Series B — investor flagged data governance as strong.
A London-based healthcare technology business commissioned a GDPR compliance audit ahead of a Series B investment round. The audit identified seven compliance gaps — including an inadequate Article 30 record, three data processing agreements that did not meet GDPR requirements, and a consent mechanism that would not withstand regulatory scrutiny. All seven gaps were remediated within eight weeks. The lead investor specifically mentioned data governance as an area where the business performed well.
7
Gaps identified
8wk
Full remediation
✓
Series B completed
Client testimony

What data and intelligence
clients say about our work.

"We had been talking about getting better visibility of our business performance for three years. Every time we looked at it, the problem seemed too complex and too expensive to address. Vistoplex's data audit broke it down into a clear, prioritised list of specific actions. Six weeks later we had a dashboard that gives us a live view of the business every morning."
MD
Managing Director
Professional Services · London
"The GDPR audit was eye-opening. We thought we were compliant — we had a privacy policy, cookie consent, some basic training. The audit identified gaps we had no idea existed. Remediating them before our investment due diligence was one of the best decisions we made in the run-up to the round. Our lead investor specifically mentioned data governance as an area where we performed well."
CE
CEO
Healthcare Technology · UK
"Our forecasting was costing us money every month in over-stock and lost sales. The Vistoplex forecasting implementation was straightforward, the model is easy for our buying team to use without statistical knowledge, and the accuracy improvement has been significant enough to measure in margin terms. The ROI case was clear within the first quarter."
CD
Commercial Director
Retail Organisation · UK
Transparent pricing

Data intelligence —
what to expect.

All Vistoplex data engagements begin with a data audit. The audit output belongs to your organisation regardless of whether you proceed. Service fees below are typical ranges for subsequent engagements, confirmed during the audit phase.

Service Entry / Audit Typical engagement range Timeline
Data strategy and architecture From £4,999 £8,000–£35,000 4–10 weeks
Analytics platform implementation From £4,999 £8,000–£50,000 6–16 weeks
Executive dashboard development From £4,999 £5,000–£30,000 3–8 weeks
Customer data strategy & CRM integration From £4,999 £5,000–£40,000 4–12 weeks
Predictive analytics and forecasting From £4,999 £12,000–£60,000+ 8–20 weeks
GDPR compliance audit and remediation From £2,500 £2,500–£12,000 2–8 weeks

All fees exclusive of VAT · Audit output belongs to your organisation regardless of whether you proceed · Free initial consultation · UK and UAE

Common questions

Data & business intelligence —
frequently asked questions.

Business intelligence is the collection of processes, technologies, and practices that organisations use to collect, integrate, analyse, and present business data to support better decision-making. It encompasses the data infrastructure that consolidates information from multiple source systems, the analytics platforms and dashboards that present that information to defined audiences, and the analytical capability to extract meaningful signals from raw data. The goal of business intelligence is to replace intuition-based decisions with evidence-based ones — giving the people making operational and strategic decisions access to the specific information they need, in a format they can act on, at the time they need it.
A data strategy is a documented plan defining how an organisation will collect, store, manage, govern, and use its data to support its business objectives. A business needs a data strategy when it is making significant decisions without adequate data to inform them, when its data is fragmented across multiple systems that do not communicate effectively, when it is planning to invest in analytics capability, or when it faces data compliance obligations requiring a structured approach to data governance. Most businesses that lack a data strategy do not lack data — they lack the architecture and governance that makes the data they already collect usable and trustworthy.
An executive dashboard is a data visualisation tool that presents key business performance metrics to senior leadership in a concise, accessible format — typically combining financial performance, operational efficiency, customer metrics, and market indicators into a single view updated at defined intervals. It works by connecting to the organisation's source data systems — CRM, financial software, operational platforms — extracting the relevant metrics, and presenting them in a visual format designed for the specific decision-making context of the leadership audience. A well-designed executive dashboard gives a leadership team the visibility they need to identify issues early, track strategic progress, and make better-informed decisions — without requiring IT involvement to compile reports manually.
CRM integration is the technical process of connecting a CRM platform to the other systems that generate and use customer data — website, marketing automation, e-commerce, support tools, and financial systems — to create a unified customer record that reflects the full history of each customer relationship. It matters because most businesses store customer data in multiple disconnected systems, meaning no single view of any individual customer relationship exists. Without CRM integration, marketing campaigns are built on incomplete profiles, sales conversations lack relevant context, and customer service interactions begin from a position of partial information. CRM integration creates the single customer record that enables all customer-facing functions to operate from the same coherent view of each relationship.
Predictive analytics is the use of statistical modelling and machine learning techniques applied to historical data to forecast future outcomes relevant to business decisions — such as customer churn probability, product demand forecasting, inventory optimisation, credit risk scoring, or sales pipeline conversion prediction. For businesses with sufficient historical data, predictive models replace intuition-based forecasts with evidence-based probability estimates, improving the quality of planning and operational decisions. The commercial value of a predictive model is determined by whether its output is specific enough to change how the business makes a decision it makes repeatedly — and whether that decision improvement generates measurable commercial benefit.
Business intelligence consultancy costs vary by scope and complexity. A data audit — the structured assessment of an organisation's current data environment — typically costs between £2,000 and £12,000 depending on the number of data sources. Analytics platform implementation typically costs between £8,000 and £50,000 for mid-market organisations. Executive dashboard development typically costs between £5,000 and £30,000. CRM integration programmes typically cost between £5,000 and £40,000. GDPR compliance audits typically cost between £2,500 and £8,000. At Vistoplex, all engagements begin with a data audit whose output belongs to the organisation regardless of whether further work proceeds.
A data audit is a structured assessment of an organisation's current data environment — documenting what data exists, where it is stored, how it flows between systems, what quality issues affect it, what compliance obligations it creates, and what analytical value it could generate if properly structured. A Vistoplex data audit produces a written findings report containing a current-state assessment, compliance gap analysis, data quality assessment, analytical opportunity identification, and a prioritised recommendations register. The audit output belongs to the commissioning organisation regardless of whether any further engagement proceeds.
GDPR governs how organisations collect, store, process, and use personal data relating to individuals in the UK and EU. UK organisations are subject to the UK GDPR and the Data Protection Act 2018. Key compliance obligations include: maintaining a record of all data processing activities, obtaining valid consent for marketing communications, responding to data subject rights requests within statutory timeframes, conducting impact assessments for high-risk processing, and maintaining appropriate contracts with third-party data processors. Non-compliance carries penalties of up to £17.5 million or 4% of global annual turnover. Most small and medium-sized businesses are less compliant than they believe — the gap between having a privacy policy and meeting the full range of GDPR obligations is significant.
Data analytics can help a small business in three primary ways. First, by giving the business owner visibility of how the business is actually performing — replacing the fragmented picture assembled from multiple disconnected tools with a single clear view of revenue, customers, marketing performance, and operational efficiency. Second, by improving the quality of specific decisions — pricing, marketing spend allocation, inventory purchasing, customer follow-up priority — with evidence rather than intuition. Third, by identifying opportunities and risks that are currently invisible — customer segments with high value potential that are being underserved, channels generating traffic but not customers, operational patterns creating cost without generating value. Most small businesses have enough data to benefit significantly from analytics — the barrier is usually the absence of the architecture and tools that make the data accessible and useful.

Start with a
data audit.

The clearest first step for any data or business intelligence enquiry is a data audit — a structured assessment that gives you an accurate picture of your current data environment, identifies the specific gaps and opportunities it contains, and produces a prioritised set of recommendations that belong to your organisation regardless of what happens next.

Most clients find the audit surfaces at least one significant compliance risk, one data quality issue affecting operational performance, and one analytical opportunity they had not previously identified. That alone typically justifies the investment.

Data audit from £2,000 · Audit output is yours regardless · Free initial consultation · UK and UAE