A caregiver looks into your fall-detection device at night on a laptop. Weeks later, the person approving it appears on another device. Standard attribution misses that gap and gives credit to the wrong channel. We rebuild measurement around how ElderTech and AgeTech purchase decisions really happen.
The Challenge
The researcher and approver rarely appear in the same session
An adult child researches at night, comparing monitoring platforms after the kids are asleep. The person who signs off – a sibling splitting the cost, or the senior pushing back if handled – is often someone else, on a different device, weeks later. Last-click credits whichever channel was open in the converting tab, never the one that built trust.
Consideration periods extend far beyond every default attribution window
A family evaluating aging-in-place platforms rarely decides in one session. The process is usually triggered by a fall, a diagnosis, or a hospital discharge, then paused for weeks while relatives compare notes and figure out who pays. Most ad platforms default to 7, 30, or 90-day windows built for retail, not multi-month family decisions. Budget shifts toward whatever caught the tail end of a decision someone else began months earlier.
The touchpoints that seal the deal take place off-screen
A discharge planner's recommendation, a call with a care coordinator, a mention from the senior's physician – these routinely do more to close a sale than any ad campaign, and none of it shows up in a CRM's default source field. Without structured capture of offline touchpoints, dashboards credit whatever channel was open at the form fill, and the referral relationships that generated the lead stay underfunded.
Churn appears to be a product failure when it's typically a health event
A senior canceling a fall-detection subscription is frequently not a sign the product failed – it's a move into a nursing facility, a hospitalization, or a death, none of which a standard SaaS churn model distinguishes from dissatisfaction. Treating every cancellation the same way sends product and CS chasing fixes that don't exist, while masking cohorts genuinely declining. LTV projections built on unfiltered churn data run wrong.
How We Can Help
We begin by mapping how your buying group navigates a decision – who searches, who approves, and the time between initial contact and signed contract – then audit what your analytics stack credits versus what sales actually heard was the deciding factor. That gap is often the biggest lever in the account.
From there, we create an attribution model designed for a multi-month, multi-person sales cycle: longer lookback windows, credit weighted across the research and approval stages, and structured tracking of offline touchpoints – care coordinator calls, facility referrals, physician mentions – so they enter the pipeline rather than a generic 'direct' bucket. This connects with our growth strategy work, since the model must reflect how the business sells.
For execution, we create two distinct funnel dashboards rather than one blended engagement metric: a caregiver acquisition funnel that tracks awareness through purchase, and a senior activation funnel that measures whether the device is worn and used. Combining them conceals real issues – caregiver signups may rise while activation quietly declines. We also reconstruct churn and LTV models to distinguish health-event cancellations from product dissatisfaction, feeding insights into related customer retention work, before handing daily operation to your marketing team – CRM fields, conversion events, call-tracking, and a cadence they can manage without an in-house data scientist.
What sets this apart is that we're operators first, connecting with product and measurement work wherever activation data requires better instrumentation, and staying embedded until the person who owns budget can defend the dashboard without us present.
What we deliver
- Multi-touch attribution model built around your real consideration window, not a generic 30-day default
- Offline touchpoint capture for care coordinator calls, facility referrals, and physician mentions
- Separate caregiver acquisition and senior activation funnel dashboards
- Churn and LTV model that isolates health-event churn from product churn
The person clicking your ad and the person signing the contract are often different people, using different devices, weeks apart. An attribution model unable to see that gap optimizes budget for the wrong buyer every time.
Our Methodology
The first 30 days focus on rebuilding the measurement foundation: auditing current tracking, interviewing sales about what closes deals, and mapping the caregiver-to-approver decision journey with CRM and call data. By day 30, we've typically identified the gap between what the stack credits and what sales already knows occurred.
Days 30 to 60 cover the model build – longer attribution windows, offline touchpoint capture, and the caregiver-versus-senior funnel split – tested against known deals, because a model that conflicts with sales won't earn trust.
The last 30 days focus on handoff: teaching whoever controls budget to defend the dashboards, establishing the reporting cadence, and adding the health-event churn flag to the cancellation system. Your team operates it once we're gone.
Our Working Process
The first 30 days focus on discovery and audit – across your CRM, ad accounts, and call logs, plus conversations with sales to understand what truly leads to a signed contract versus what the dashboard credits. Days 30 to 60 cover the model build, tested against actual deals. Days 60 to 90 focus on rollout and training, finishing with a dashboard owned by your team.
On our side, the build is managed by a lead strategist and an analytics operator. On your side, we require access to the CRM and ad platforms, one hour each week from the person responsible for pipeline visibility, and several interviews with staff who speak directly with families. Meetings are weekly throughout the build, shifting to biweekly after dashboards go live.
Most engagements last three to four months, with some continuing as an ongoing retainer: uncomfortable in month one as the audit validates gaps nobody wanted validated, building during month two, and trusting the figures by month three. If you can't determine whether a dollar spent three months ago affected the contract signed last week, we should talk.
- Attribution accuracy across multi-month decisions
- Caregiver and senior funnel visibility
- Cleaner LTV and churn modeling
- Offline touchpoint capture and crediting
If your eldertech / agetech company needs marketing analytics leadership, we should talk.
Expand your marketing team output with our experts
Let us take a custom approach to your growth goals by assembling and leading the best-in-class marketing team to support your next stage.
Frequently asked questions
What does a marketing analytics engagement cost for an ElderTech or AgeTech company?
Pricing depends on the number of data sources that require integration – CRM, ad platforms, call tracking, product usage – and how far the existing tracking is from being usable. It's typically less expensive than hiring a full-time analytics employee, and more accountable than a generalist agency using the same template for every client. The main factor is whether offline touchpoints are already tracked in a structured way.
How soon will we see results from a marketing analytics engagement?
The audit reveals actionable findings within the first 30 days, typically the gap between what your dashboard credits and what sales already knows closed the deal. The reconstructed attribution model and funnel dashboards usually go live by day 60. Since consideration windows last from weeks to months, allow at least one complete sales cycle before fully trusting the model for budget decisions.
How does the marketing analytics team work with our current marketing and sales staff?
We operate within your current CRM and ad accounts instead of creating a separate system that nobody uses. Weekly meetings during the build keep your marketing lead and the person responsible for the sales pipeline informed. After dashboards go live, we teach your team to operate and defend them, then shift to a biweekly cadence rather than remaining embedded forever.
What differentiates Winston Francois from a standard marketing analytics agency?
Most agencies use the same attribution template no matter how a business sells. We begin with real buying behavior – two people, two devices, offline referrals, health-driven churn – and create a model that reflects it. We're operators who have managed growth functions ourselves, not consultants who deliver a dashboard and vanish.
How is ROI measured when consideration windows span multiple months?
We lengthen attribution windows to reflect your real sales cycle rather than a platform default, then weight credit between the caregiver's research stage and the approver's decision stage. Offline touchpoints are coded into that same pipeline so referral channels receive proper credit. Reporting then follows a monthly or quarterly cadence, rather than a weekly view unable to capture a decision that's still underway.
What kind of ElderTech or AgeTech company is best suited to this service?
This service suits Series A through growth-stage companies, approximately $5M to $100M in ARR, where marketing spend has grown enough for an incorrect attribution model to actively misdirect budget. It's a strong fit if your team believes the dashboard conflicts with what sales hears from families, or when caregiver acquisition appears healthy but senior activation shows another picture. We begin with a working session that compares conversion paths with deals sales recalls closing.
