Insights

Guides, comparisons, analysis and explainers for marketing teams.

Marketing budget allocation: fund the next useful decision
Start with what your business needs next, then work out what your team can actually deliver.
Martech stack audit: decide what to keep, fix or retire
A martech stack audit should tell you which tools earn their keep, which need fixing and which you can retire.
B2B landing page optimisation: improve qualified conversion, not form volume
A B2B landing page should help the right people take the next step.
Email deliverability for marketers: fix the system before the subject line
Getting an email accepted by a server doesn't mean it reached the inbox.
UTM naming conventions: a campaign tracking system people will use
UTM tags tell your analytics system where a visit came from and which campaign brought it in.
Marketing data quality audit: start with the errors that change decisions
Start a marketing data audit with the errors that cause trouble: the enquiry sent to nobody, the customer counted twice or the ...
Lead scoring for B2B marketing: keep fit and engagement separate
Keep fit and engagement separate in B2B lead scoring.
CDP vs CRM vs data warehouse: choose around the customer task
Your CRM helps people manage customer relationships.
Marketing attribution vs MMM vs incrementality: which question are you asking?
Attribution divides up credit for the interactions you can track.
Marketing incrementality testing: find out what the campaign changed
Would those customers have bought anyway?
Display advertising quality: what to check beyond cheap CPMs
A low CPM means you bought impressions cheaply.
Webinar follow-up: turn audience questions into useful next steps
Follow up on what people actually asked for.
Event marketing ROI: measure what happens after the badge scan
Event marketing ROI compares the financial return you can reasonably credit to an event with everything it cost to run.
B2B intent data: verify the signal before you buy the story
B2B intent data can give you a reason to investigate an account.
ABM account selection: build a target list sales can defend
Choose ABM accounts your business can serve well, then look for a relevant problem and a realistic way to reach the people ...
SEO performance measurement: why average position can mislead
Read SEO performance by relevant queries and pages, alongside clicks and impressions.
GEO for marketing teams: make content useful enough to cite
GEO starts with content that answers a real question and gives people a reason to trust the answer.
AI content repurposing: turn one webinar into useful editorial work
Start with something worth saying, not a target for how many assets to produce.
AI agent governance for marketing: permissions before autonomy
Decide what an AI agent may do before you connect it to live marketing systems.
AI marketing ROI: measure the cost of work you can actually use
AI marketing ROI tells you whether the work you get back is worth what you spend.
Zero UI: what marketers should evaluate
Zero UI means using voice, gestures or automation instead of relying on a screen.
Choosing Claude for a marketing team
Choosing Claude for a marketing team starts with the work, not the model name.
ChatGPT pricing: a guide for marketing teams
The ChatGPT subscription is only part of the bill.
The role of data in AI for marketing
AI works with the examples and information you give it.
Generative AI and critical thinking in marketing
AI can produce a convincing answer before you've had time to question it.
Generative and multimodal AI: differences and marketing uses
Generative AI creates content.
What is Claude AI? Marketing uses and practical limits
Claude is Anthropic's AI assistant.
Machine learning for marketers: uses and evaluation
Machine learning spots patterns that can help you predict responses or group audiences.
AI avatars and Web3: evaluating customer engagement
An AI avatar can present information or guide a conversation; a Web3 component may handle ownership or access.
What is artificial intelligence? A guide for marketers
AI uses computer systems to do tasks such as recognising patterns, generating content and making predictions.
Marketing data integration: campaigns, CRM and reporting
Marketing data integration connects campaign, contact and customer records across your tools.
How to run an AI pilot for a marketing team
An AI pilot should end with a decision: use it, change it or stop.
AI-assisted research for marketers: sources and verification
AI can help you find leads, organise notes and compare sources.
AI agents in marketing operations: where to start
Start with a marketing job you can clearly describe and check, such as preparing a campaign report.
How AI agents work: a guide for marketers
An AI agent uses a model, instructions and tools to work through a task.
Meta AI memory: what personalization means for marketers
An AI assistant remembering someone's preferences doesn't mean an advertiser can see or use them.
Data quality tools: what marketing teams should compare
Choose a data-quality tool by giving it the problems already in your CRM: duplicates, missing fields and records that disagree.
Customer experience analytics: turning feedback into action
Customer experience analytics helps you see where people struggle and decide what to change.
CRM for marketing teams: tools and lead handoffs
A marketing CRM should help you understand who enquired, where they came from and what happened next.
Low-code and no-code for marketing operations
Low-code and no-code tools can take routine work off a marketing team's hands without a large development project.
Data warehousing: marketing use cases across industries
A data warehouse brings records from different systems together so you can analyse them.
Data mining for marketing: finding patterns worth testing
Data mining looks for patterns worth investigating: products bought together, similar customer behaviour or an unexpected change in response.
Computer vision in retail: marketing uses and evaluation
Computer vision can help shoppers find similar products and help retailers organise their catalogues.
Where data science helps marketing decisions
Data science earns its place when it helps you make a better decision.
AI chatbots for marketing: useful journeys and handoffs
A useful chatbot helps someone get an answer or reach the right person.
Data science for marketing: from analysis to action
Marketing data science starts with a question, turns the available records into usable evidence and tests what the answer means.
SaaS buying for marketers: pricing, AI features and fit
The headline SaaS price rarely tells you what a marketing tool will cost to run.
NLP for marketing: feedback, sentiment and search
Natural language processing helps you work with customer comments, survey replies and other text.
Data visualization for marketers: choosing the right chart
Choose a chart that makes your question easier to answer.
No-code payment workflows: a guide for marketing teams
A no-code payment workflow can tell your marketing systems that a purchase succeeded, failed or was refunded.
Big data vs small data: choosing marketing evidence
You don't always need more data.
Marketing analytics: turning reports into decisions
Marketing analytics should help your team decide what to do next.
VR and AR in marketing: evaluating product experiences
VR puts someone inside a digital environment; AR adds digital elements to the world they can see.
Marketing data: management, analytics and data science
Data management keeps your records usable.

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