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Proportione · Research · ProVisio LineUpdated October 19, 2026 · ← All lines

ProVisio Line

Business intelligence with generative AI, using the data you already have

Summary. Your company generates a digital footprint every day (searches, website, campaigns, networks) and stores years of data in its management software. ProVisio investigates how to translate all of that into your industry's indicators, in a dashboard that a manager can read without being an analyst. Design, construction, and evaluation with Design Science Research.

Keywords: business intelligence · generative AI · SMEs · industry KPIs · Design Science Research

works in this line
6
with open-access DOI
3
countries (ES · PT)
2
CIDEMA 2025 proceedings and thesis presentation at the DBI Research Summit, both with DOIs.

1What the line is

From digital signal to sector KPI

An SME accumulates signals, but that footprint does not speak the language of its decisions. ProVisio steps into that gap: it gathers the signals, organizes them with a Signal × KPI scheme, and turns them into a readable dashboard.

The research covers the complete Design Science cycle: literature review and bibliometric mapping of the field, artifact design, construction, and evaluation with real companies.

Acquisition
Revenue
Retention
Awareness
Efficiency
Searches
S1·K1
S1·K2
S1·K3
S1·K4
S1·K5
Web Analytics
S2·K1
S2·K2
S2·K3
S2·K4
S2·K5
Paid Media
S3·K1
S3·K2
S3·K3
S3·K4
S3·K5
Social content
S4·K1
S4·K2
S4·K3
S4·K4
S4·K5
Figure 1 · Signal × KPI Scheme: four families of digital signals crossed with five families of business indicators. Source: own elaboration, Proportione.

2Findings

What we have learned

  1. H1Translation, not integration

    The BI bottleneck in SMEs is not connecting the data, but translating heterogeneous signals into the KPIs of each sector.

  2. H2A grid that makes the decision explicit

    Crossing signal families with indicator families makes it clear which signal feeds which decision.

  3. H3Code calculates; the model drafts

    No figure comes out of the language model. If a number cannot be traced back to its calculation, it does not enter the dashboard.

3Publications

The work, as published

First page: From market signals to decisions: integrating search engine data into SME business intelligence

CIDEMA 2025Madrid · ES · EN

Conference paper · Proceedings · ISBNOpen access · CC BY-SA 4.0

From market signals to decisions: integrating search engine data into SME business intelligence

Javier Cuervo, Rui Pedro Figueiredo Marques

Download PDFDOI10.5281/zenodo.18010664
Cite

Cuervo, J., & Marques, R. P. F. (2025). From market signals to decisions: integrating search engine data into SME business intelligence. II International Scientific Congress CIDEMA. https://doi.org/10.5281/zenodo.18010664

CAPSI 2026Coimbra · PTFrom digital signals to sector-specific KPIs: an LLM-mediated BI artifact for SMEsJavier Cuervo · Rui Pedro Figueiredo MarquesIn press · proceedings in preparation

CAPSI 2026Coimbra · PT · EN

Conference paper · Peer-reviewed

From digital signals to sector-specific KPIs: an LLM-mediated BI artifact for SMEs

Javier Cuervo, Rui Pedro Figueiredo Marques

In press · proceedings in preparation
$ pip install proportione-prisma
$ prisma ingest openalex --query "…"
$ prisma screen --rules rules.yaml
$ prisma extract --pdfs data/pdfs/
# PRISMA 2020 · MMAT 2018 · bibliometrics

Zenodo · GitHubOpen source · EN

Software · MIT licenceOpen access · MIT

PRISMA: A Python Toolkit for Systematic Literature Reviews

Javier Cuervo, Rui Pedro Figueiredo Marques

View on ZenodoDOI10.5281/zenodo.19883809
Cite

Cuervo, J., & Marques, R. P. F. (2026). PRISMA: A Python Toolkit for Systematic Literature Reviews. Zenodo · GitHub. https://doi.org/10.5281/zenodo.19883809

Open source of the artifact: github.com/Proportione/proVisio (Apache-2.0).

4Full record

All ProVisio publications

2025–26

  1. In press

    Conference paper · ProVisio

    From digital signals to sector-specific KPIs: an LLM-mediated BI artifact for SMEs

    CAPSI 2026 · Coimbra · PT · 8 oct 2026 · Javier Cuervo, Rui Pedro Figueiredo Marques

    In press · proceedings in preparation

  2. Abstract · ProVisio

    Designing ProVisio: a generative-AI-augmented BI artefact for SME decision-making

    Research Summit UA 2026 · Aveiro · PT · jul 2026 · Javier Cuervo, Rui Pedro Figueiredo Marques

  3. In press

    Book chapter · ProVisio

    Where search data meets business intelligence: a bibliometric mapping of the Ibero-American landscape

    CIDEMA · McGraw Hill · Madrid · ES · 2026 · Javier Cuervo, Rui Pedro Figueiredo Marques

    Accepted · in production
  4. { }

    Software · ProVisio

    PRISMA: A Python Toolkit for Systematic Literature Reviews

    Zenodo · GitHub · Open source · 29 abr 2026 · Javier Cuervo, Rui Pedro Figueiredo Marques

    View on ZenodoDOI10.5281/zenodo.19883809

  5. Conference paper · ProVisio

    From market signals to decisions: integrating search engine data into SME business intelligence

    CIDEMA 2025 · Madrid · ES · 19 Nov 2025 · Javier Cuervo, Rui Pedro Figueiredo Marques

    Download PDFDOI10.5281/zenodo.18010664

  6. Presentation · ProVisio

    Business intelligence for strategic decision-making: a digital analytics approach for innovation in SMEs

    DBI Research Summit 2025 · Aveiro · PT · 22 Jul 2025 · Javier Cuervo

    Download PDFDOI10.5281/zenodo.17245495

Full record at ORCID 0009-0006-7134-2894. Works under review are not listed until a decision is made.

5Who signs

Authors

Javier Cuervo

Javier Cuervo

Co-founder and CTO of Proportione · Ph.D. candidate in Business Innovation, Universidade de Aveiro (DEGEIT) · Professor at UNIE

RM

Rui Pedro Figueiredo Marques

ISCA-UA · GOVCOPP, Universidade de Aveiro · Thesis director and co-author

6Continue reading

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