Vaitom is Digitata's behavioural intelligence platform for mobile operators and MVNOs. Two engines on one behavioural core: Vaitom CVM for subscriber-level segmentation, journeys and campaigns, and Vaitom Dynamic Pricing for real-time, AI-optimised tariffs that fill idle network capacity and defend against price wars.
In competitive markets, headline pricing converges within weeks and every operator ends up selling the same megabyte at the same price. Discounting protects share for a quarter and destroys margin for a year.
Vaitom takes the opposite route. It reads what subscribers actually do - recharge rhythm, usage timing, location, response to offers, elasticity to price - and turns that into two levers that compound: the right offer to the right subscriber, and the right price at the right time in the right cell.
Static price plans ignore that the same subscriber values a megabyte differently at 8am and at 2am.
Network built for peak sits empty off-peak. Unsold capacity is a perishable asset.
Mass sends train subscribers to ignore you and erode the value of every future message.
Dormancy builds over weeks of small behavioural shifts that monthly reporting never surfaces in time.
Every subscriber event - CDRs, recharges, data sessions, network performance, campaign responses - lands in a single behavioural profile. Both engines decide from the same truth, so pricing and marketing never contradict each other.
Customer value management built on revealed behaviour, not declared preferences. Subscriber 360 profiles, smart-attribute segmentation, lifecycle journeys, campaign execution across every channel, and real-time measurement of what each intervention actually returned.
Digitata's Dynamic Tariffing heritage, productised. Price is recalculated continuously against network congestion, time of day, location and subscriber elasticity - moving demand off peak, monetising idle capacity, and giving commercial teams a weapon in a price war that competitors cannot simply copy.
Every subscriber gets a continuously updated profile derived from transaction and network behaviour. No surveys, no declared preferences - only what the subscriber actually does.


Marketing teams build precise cohorts themselves - combining raw attributes, calculated behavioural metrics and AI-generated scores - and see segment size and revenue exposure before a single message is sent.
The right offer, to the right subscriber, at the right moment - executed continuously rather than on a monthly campaign calendar.
Journeys fire on behaviour - a missed recharge cycle, a first data session, a dormancy signal, a competitor-shaped usage drop - not on a date.
The recommender picks bundle, price point and validity per subscriber from their elasticity and usage profile, within commercial guardrails.
Frequency caps, quiet hours, channel fatigue rules and priority arbitration stop subscribers being over-messaged across teams.
Every journey runs with holdout control. Winning variants promote automatically; losers retire.
Pre-built dormancy and churn-risk journeys with personalised incentives sized to the subscriber's value, not a flat discount.
Guided progression from small denominations to higher-value bundles as behaviour and trust build.
Vaitom does not force subscribers into a new app. It publishes decisions into whatever channel already reaches them - including the low-bandwidth channels that dominate prepaid markets.
Any channel can ask Vaitom a single question - what should this subscriber see right now? - and receive the offer, the price, the copy and the reason code, in milliseconds, with the interaction logged back into the behavioural profile.
Return on investment is measured against control groups as campaigns run, so commercial teams can stop what isn't working the same day rather than at the next review.

Network capacity is perishable. Vaitom Dynamic Pricing continuously re-prices voice and data against live congestion, time and location, shifting demand into empty hours and empty cells, and turning capacity you already paid for into revenue.
CDRs, charging records, network performance statistics and cell-level congestion feed the pricing engine continuously across multi-vendor networks.
Machine learning estimates demand elasticity per segment, per location, per hour - how much extra usage a given discount will actually buy.
The engine solves for the operator's objective - revenue, margin, load balancing or share defence - inside floors, caps and regulatory rules.
New prices are broadcast to subscribers via cell broadcast, USSD, SMS or app, so the subscriber sees the discount where and when it applies.
Charging systems apply the live price; realised behaviour flows straight back into the elasticity models for the next cycle.
Discount at cell or zone level - stimulate usage where capacity is idle and hold price where the network is full.
Move price-sensitive demand into off-peak windows and unlock revenue from hours the network is otherwise idle.
Prices tighten automatically as a cell fills, protecting customer experience and capex planning at the same time.
Different subscribers get different curves - heavy data users, dormant prepaid, high-value voice - each priced on its own response.
Respond to a competitor's headline cut with targeted, temporary, geographically precise pricing instead of a base-wide margin sacrifice.
Floors, caps, blackout periods, regulatory constraints and margin thresholds are hard limits the optimiser cannot cross.
The same platform, deployed at two very different scales - a national operator with its own network and charging estate, or a lean MVNO team running on a host network.
| Objective | For an MNO | For an MVNO |
|---|---|---|
| Revenue stimulation | Fill idle cells and dead hours with congestion-linked dynamic pricing across the national footprint. | Optimise bundle mix and price points against wholesale cost, without owning the network. |
| Retention | Behavioural churn signals across tens of millions of prepaid subscribers, with automated win-back journeys. | Early dormancy detection on a smaller base where every subscriber lost is materially felt. |
| ARPU growth | Personalised step-up offers sized to each subscriber's demonstrated elasticity. | Targeted upsell into higher-value plans and data add-ons through existing digital channels. |
| Price competition | Precise, temporary, location-specific responses instead of base-wide cuts. | Differentiate on relevance and experience where headline price cannot be matched. |
| Team capacity | Fewer manual campaign cycles; analysts move from building lists to designing strategy. | Marketing, pricing and analytics capability without the headcount to build it in-house. |
Vaitom integrates into complex, multi-vendor telco environments - the ones with three access-network suppliers and three charging systems - and it runs where your data is allowed to live.
A Tier 1 West African operator's Dynamic Tariffing deployment required interfaces to performance statistics and cell broadcast for three different access-network suppliers, CDR processing from three IN charging systems, and a new cell broadcast controller. It was delivered in six weeks - against an expectation of six months.
"The most powerful pricing innovation since the inception of mobile telecommunications, with a capacity to transform the fortunes of operators in very competitive markets. Executed effectively it delivers subscriber growth, ARPU stimulation, retention and loyalty - and it is a strong tool for fighting price wars."
"Zone helped us grow revenues in the dead hours - midnight to 6am - from US $300k to US $1.5m per month."
Tell us about your market, your base and your pricing constraints. We'll show you where Vaitom finds revenue in your network - and what it takes to get there.