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Novistu

Service : automate

What happens after someone becomes a customer.

Customer lifecycle automation segments customers by actual behaviour, recency and value, then runs the right message on the right channel at the right time: welcome, reactivation, loyalty reward, renewal reminder, win-back. Novistu builds this on top of your CRM/ERP and messaging channels, so retention becomes a system instead of an occasional campaign.

The mechanism

Most agencies stop at the sale.

Typical stackWhatsApp Business APIEmail (SES / Postmark)Push (FCM / APNs)ERPNext / Frappe CRMn8nPostgreSQL

The problem

What this fixes

01

Every customer gets the same message

A new buyer, a loyal regular and someone who has not ordered in six months all land in the same broadcast. The message that would move each of them is different, and sending one blast ignores that.

02

Good customers are easy to lose quietly

Without a trigger for declining recency or frequency, a customer going cold looks identical to one who is simply between purchases, until they are gone.

03

Campaigns are not measured past 'sent'

Reach and opens are not revenue. Without tracking redemption, repeat purchase and attribution back to the message, nobody can tell which campaigns are actually working.

How we build it

Principles before code.

01

Segment by behaviour, not guesswork

Recency, frequency, monetary value, product preference, channel preference and lifecycle state (new, active, loyal, at-risk, dormant) define segments from your real data, not assumed personas.

02

Orchestrate journeys, not one-off sends

A customer going quiet triggers an eligibility check, a segment-appropriate offer and a channel decision, automatically, rather than waiting for the next scheduled campaign.

03

Match message to channel on purpose

WhatsApp, email, push and SMS each fit a different moment and consent level. The system picks the channel a customer actually responds on and respects opt-outs everywhere.

04

Measure redemption, not sends

Every campaign is tracked to response, redemption, repeat purchase and revenue contribution by segment, so budget moves toward what actually retains customers.

Delivery

From first call to running system.

  1. 01

    Map

    Audit customer data, current campaigns and consent state; define segments and the journeys worth automating first.

    1 to 2 weeks
  2. 02

    Build

    Segmentation, messaging orchestration and analytics wired to your CRM/ERP and channels, tested on real cohorts.

    3 to 5 weeks
  3. 03

    Pilot

    One or two journeys (commonly reactivation and welcome) measured against a held-out control group.

    3 to 4 weeks
  4. 04

    Scale

    Full lifecycle rollout with dashboards, and monthly tuning of segments, offers and timing.

    Ongoing

What you get

  • Behavioural segmentation model built on your CRM/ERP and order data
  • Lifecycle journeys: welcome, reactivation, loyalty reward, renewal reminder, win-back
  • WhatsApp, email and push orchestration with frequency and consent controls
  • Targeted offer logic: right customer, right message, right channel, right time
  • Campaign analytics: reach, redemption, repeat purchase, retention by segment
  • Suppression and do-not-contact handling shared with sales and support systems

Questions

Asked before every build.

Grouping customers by what they actually do (how recently, how often, how much, what they buy, which channel they respond on) instead of by industry stereotypes. A new customer, a loyal repeat buyer and someone who has gone quiet are three different segments needing three different messages.

It overlaps, but the emphasis is different: it is built on the same lead and customer data as your sales and support systems, so a customer's history, consent state and do-not-contact preference are shared across all of them, not siloed in a separate marketing tool.

Sales AI covers the pre-sale journey: capture, qualification, follow-up and the CRM record up to a closed deal. This covers what happens after: keeping customers engaged, catching churn early and running win-back, on the same underlying data.

It is designed against that: frequency caps, explicit opt-out handling, suppression lists and segment eligibility checks before anything sends. The goal is fewer, better-targeted messages, not more volume.

You need enough repeat-purchase behaviour for segments to be meaningful, usually a few hundred active customers or more. Below that, a simpler manual approach is more honest, and we will tell you if that is your situation.

Tell us what is eating your team's hours.

A short brief, answered within one working day. The first call is free, and if AI is not the right answer, we will say so on that call.

First call free : honest about fit : no obligation