Advanced actions to optimise and scale

Strategy & Journeys

Strengthen and expand your workflows across the lifecycle.

You likely already have a few flows in place and regular manual campaigns. Now the focus should shift to building structured workflows for every key stage: lead nurture, activation, retention, and reactivation.

Use this framework to design or improve each journey:

• Analyse behaviour: Look at what actions activated or retained users took early on.

• Identify core segments: Tailor journeys to different customer types or behaviours.

• Implement retargeting: Re-engage users who didn’t complete critical steps (e.g. KYC, first payment).

• Educate and inspire: Share tutorials, case studies, or success stories to build confidence.

• Optimise with data: Track user behaviour and campaign performance and optimise campaigns accordingly.

At the advanced level, the goal is to expand workflows to 15–30 campaigns per stage, using conditional paths and behavioural triggers to personalise the journey. Orchestrate journeys across email, SMS, in-app, and push for a seamless user experience. At this stage, it’s not just about “having flows”, it’s about creating a cohesive, automated system that adapts in real time.

Expected results from optimising this:

• 30–50% higher retention rates by guiding users with advanced multi-touch journeys instead of generic flows.

• 15–25% increase in Customer Lifetime Value (LTV) as workflows keep users active and engaged longer.

• 20–30% reduction in churn/drop-offs at critical lifecycle points (onboarding, KYC, renewal).

• Predictable, scalable growth, as real-time, multi-channel workflows continuously adapt to user behaviour.

Segmentation & Personalisation

From lifecycle segments to hyper-personalisation at scale.

You’re likely already segmenting by lifecycle and product. The next step is to layer in advanced data:

• Behavioural triggers → adapt content in real time based on actions (e.g. transaction type, feature usage).

• Motivational drivers → message differently based on user goals (saving, investing, growing a business).

• Dynamic content blocks → build one campaign that serves multiple variants automatically.

• Advanced segmentation models: Go beyond manual groups; use data to uncover hidden patterns, like which customers are most valuable, at risk, or primed for upsell.

• Predictive models → forecast churn risk, likelihood to convert, or upsell potential — and personalise journeys accordingly.

The goal is hyper-relevance without manual effort, advanced personalisation systems where every user’s journey feels uniquely theirs.

Expected impact from optimising this:

• 20–40% higher engagement rates from dynamic content.

• 10–15% lower churn, as customers feel consistently understood and supported.

• Scalable personalisation: Advanced journeys without bloating your marketing team.

Deliverability & Set-Up

From healthy hygiene to proactive deliverability leadership.

You’ve likely already implemented authentication and exclusion rules. Now move toward advanced deliverability management:

• Monitor reputation daily with tools like Google Postmaster & Postmark.

• Benchmark against industry spam complaint rates (<0.1%) and maintain consistent suppression strategies.

• Test regularly across multiple inboxes and ISPs to detect subtle deliverability shifts early.

• Automated list hygiene: Use deliverability tools like Validity to automatically clean your lists, remove bounces, and catch risky addresses before they hurt your sender score.

• Proactively rotate domains/subdomains for campaigns, lifecycle, and transactional streams.

At this stage, deliverability isn’t just a safeguard; it’s a competitive advantage ensuring every campaign reaches its audience.

Expected impact from optimising this:

• Inbox placement consistently 98%+, even at scale.

• Minimal complaint/bounce rates, ensuring long-term sending health.

• Ability to scale email volume confidently, without risking sudden drops in deliverability.

Performance & Reporting

From tiered reporting to predictive, revenue-driven optimisation.

You’re already tracking beyond opens and clicks, with at least some tiered reporting in place. The next step is to go deeper and make reporting predictive:

• Commercial metrics (Tier 1): Go beyond LTV and retention rate, model how CRM/email contributes to revenue growth and churn prevention.

• User metrics (Tier 2): Run cohort analysis to track activation, frequency, and churn patterns across different customer segments.

• Campaign metrics (Tier 3): Use open, click and unsubscribe rates as diagnostics, but also connect them back to user and commercial outcomes.

Layer in predictive analytics and automation:

• Use churn-risk scoring to identify customers most likely to drop off.

• Prioritise high-value segments with revenue attribution models.

• Expand testing from subject lines to entire journey experiments (e.g. A/B/C testing onboarding flows).

• Automate weekly dashboards and monthly deep dives to spot areas of risk, optimisation, and new growth opportunities.

At this level, performance management isn’t just about measuring; it’s about turning CRM/email into a forecasting engine for growth.

Expected impact from optimising this:

• 15–25% higher ROI from CRM/email, as optimisation is tied directly to revenue and churn reduction.

• Earlier detection of risks, reducing churn spikes before they happen.

• More efficient allocation of spend and resources, guided by predictive modelling.

• Continuous optimisation at scale, with weekly pulse checks and monthly strategic reviews driving long-term improvements.