How Russian ERP platforms appear in the algorithmic choice of CIOs in Russia
CIO of an industrial holding · moving to a domestic perimeter
68 out of 100 — this is how much the object influences the choice in this scenario0 — the buyer never sees you, 100 — you are recommended first
The choice happens right here.
On a specific scenario and in the relevant languages we show where the company holds a strong position and where it starts to lose it.
Pick a company and find out why it loses the position, who takes its place, what the economic effect is and what can be changed.
The category has no standalone public report: the value is derived from the parent market by segment share, so it is directional rather than exact.
Choice scenarios
The scenario is the economic task being measured. It sits below the market: each market has its own scenarios. Switching it recomputes the stages of choice, the point of maximum loss, the journey comparison, and the forecast under “Points of intervention”. The key finding, the loss factors, and the competitors belong to the measurement as a whole.
Language is a run condition, not a separate scenario: the same economic task is asked in the local language and in English. The gap between them is visible in the raw observations at the bottom of the page.
Compare the scenarios across journeys →Passing the stages of choice
Share of AI-system answers where the object passes each stage of choice and stays in the buyer's consideration field. The early stages make up the Participation Index, the shortlist and recommendation — the Win Index.
Measurement conditions: S1 «A holding's move to a domestic ERP» · journey «Problem-first» · Russia · languages RU, EN · AI systems: 7 · Q1 2026
Height of a column is the share of answers where the object passes the stage. The narrowing between columns is the loss.
A stage is analytical markup of a step, not a required order of conversation: a journey may start with a recommendation and come back to comparison.
At home 1C is named first and reaches the recommendation: departed vendors are mentioned as unavailable, while the open questions concern the scale of holding-level deployments.
The largest loss occurs between the stages «Shortlist» and «Recommendation» −12 pp for 1C on the selected journey.
Why the position is lost
Choice factors that keep the object out of the final recommendation.
Position depends on the journey and on the scenario
Probability of a final recommendation for 1C for each decision journey, in both scenarios.
The scenarios are different economic tasks. Their levels may be set side by side but not subtracted: the gap between scenarios is not a deficit to be closed.
Who takes the place
Tile area and colour show the win index on this market — shortlist and recommendation. The participation index is in the table view.
What implementation givessample analysis
Each hypothesis is a verifiable action with a forecast of the index gain. Approve the ones you take on — implementation starts from your confirmation.
- 01loss factor · 52% of answers
Publishing holding-scale load tests will settle the main question of the evaluation stage.
Questions about performance at holding-scale load
Forecast+5pts to the indexEconomic potential≈ $5 mn / year - 02loss factor · 44% of answers
Architecture case studies of large deployments will redefine the product category in AI answers.
Few public deployments with a disclosed architecture
Forecast+4pts to the indexEconomic potential≈ $4 mn / year - 03loss factor · 37% of answers
An open map of integrators for large projects will add a trust signal ahead of the shortlist.
The time and cost of migrating off the Western platform are unclear
Forecast+3pts to the indexEconomic potential≈ $3 mn / year
How the forecast is calculatedforecast · model
This is a sample analysis for an object that entered the universe of this measurement. The universe is assembled anew at every scan of the category: its composition and the positions within it may change. Forecast, not a measurement. The upper bound is the loss at the narrowest transition, distributed across the weights of the loss factors; stage-passing points are carried into index points one to one, and the conversion coefficient is not yet established by the methodology. The money figure uses a working calibration: CCI is measured inside the category universe rather than against the whole market, so 25 index points are taken as roughly 2 percentage points of market share. The actual gain is obtained empirically only — by repeating the same benchmark after the intervention.
Check the conclusions against the raw observations
Study the data, reproduce the conclusions or find what we missed.
How the measurement works- 170
- observations
- 7
- AI systems
- 2
- languages · RU, EN
- Q1 2026
- measurement
ERP × Russia
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Photo: Carl Lender (CC BY 2.0), Retired electrician (CC0)