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M4 - Second iteration of interviews, user persona and use cases

Second iteration of interviews

How we conducted the interviews

We decided to conduct the second round of interviews to validate our assumptions and gather more insights about our potential users. We decided that the first set of questions were a good starting point for gathering information so we kept them and just tried to talk to some more business owners.

We interviewd 2 more business owners from different fields: a bagel shop and tourism agency.

  • Together Travel - agentie de turism

    Click to expand

    Q: Cum știți cata publicitate sa faceti pentru a atrage clientii si unde?

    A: In primul rand, nu stim cata sa facem, am incercat peste tot si am ajuns la concluzia ca pe Facebook si Instagram merge cel mai bine. Cata publicitate facem… asta depinde de buget, cand avem mai multe fonduri mai invesitm si in reclame platite pe Facebook.


    Q: Contorizati în vreun fel ce se cere mai mult? Ce fel de vacante, in ce loc sau in ce perioada a anului?

    A: Da, avem un excel in care trecem toti clientii cu toate ofertele pe care le facem fiecaruia, bine, in mare parte, nu chiar cu toti, cam 70-80% din ei.


    Q: Ati spus ca tineti evidenta vanzarilor într-un excel, folositi si altfel de aplicatie?

    A: Avem si un CRM, dar e mai simplu in excel.


    Q: Ce solutii digitale folositi pentru a analiza cerintele clientilor?

    A: Excelul. Nu avem atat de multe date incat sa avem nevoie de tooluri. CRM-ul pe care il folosim ne arata si niste rapoarte, dar din nou, nu sunt atat de multi (clienti) incat sa avem nevoie de CRM. Plus ca locatiile sunt de obicei destul de putine, sunt de obicei unde sunt zborurile charter, asa ca e simplu sa ne dam seama cine, ce cere. Uneori dureaza mult sa gasim ceva ce le place clientilor pentru ca vad un anunt dar se razgandesc si este destul de costisitor ca timp sa le gasim altceva, dar nu ai ce face, daca nu vrei sa ii pierzi trebuie sa ai rabdare.


    Q: S-a intamplat vreodata sa aveti perioade in care cererea era aproape inexistenta sau semnificativ redusa? A fost ceva la care v-ati asteptat? Si daca da cum ati prevazut acest moment?

    A: Da, acum, lunile octombire, noiembrie si decembrie. Ne-am asteptat pentru ca suntem influentati de concediile oamenilor, oamenii pleaca toti in concediu vara, si de vacantele copiilor pentru ca cei mai multi sunt familii cu copii care pleaca atunci cand au copiii vacante.


    Q: Credeti ca v-ar ajuta un tool care sa va analizeze datele din excel si sa va ofere anumite informatii suplimentare?

    A: Daca am avea mai multi clienti ar deveni complicat sa analizam noi de mana datele, atunci cred ca am apela la ceva din ce spuneti, poate daca am avea 500 de clienti pe saptamana.


    Agentie de turism

  • Mara Pizzerie - Bagel shop and pasteries

    Conversatie in timp ce asteptam ce ii cerusem - am mentionat ca o voi intreba cate ceva pentru un proiect la facultate Click to expand

    Q: Cum stiti cate prajituri/pateuri sa faceti?

    A: In functie de ce cumpara clientii, daca dimineata se vand mai multe prajituri, mai facem peste zi


    Q: Dar seara mereu vad vitrina destul de plina (trec des pe acolo), nu ramaneti cu multe produse?

    A: Ba da, dar ce sa facem, trebuie sa avem


    Q: Cu marfa cum faceti din moment ce mai mariti stocul de prajituri si pateuri peste zi?

    A: Ne mai luam de la magazinele din vecinatate daca e mare nevoie


    Nota: aveau laboratorul in aceeasi locatie - nu le aduceau de undeva => pierdeau timp sa faca peste zi ceea ce se vindea mai bine + aruncau ce ramanea nevandut la final de zi.


    Mara Pizzerie

After conducting these interviews we gathered more insights that confirmed our initial assumptions: small business owners struggle to analyze their sales data and make informed decisions due to lack of time, expertise, and resources. But in the same time there are small busienesses that already use some digital tools to help them with this process and want to improve their data analysis even more who need a simple, yet effective solution.

👤 User Persona

User persona: The busy local business owner

Name: Maria Popescu
Age: 42
Role: Owner of a small bakery
Tech comfort level: Low to moderate
Business size: 4 employees

Tools she currently uses:

  • Cash register/POS system
  • Excel (very basic use)
  • Inventory notebook
  • Sometimes Facebook/Instagram for promotion

Goals:

  • Predict how much to bake - without wasting too much of the ingredients
  • See simple patterns - slow days, peak hours, seasonal items
  • Make decisions faster
  • Keep the business profitable

Pain points:

  • Existing tools feel overwhelming and complex + little tech knowledge
  • No time to dig through POS reports or spreadsheets
  • Intuition-based decisions often lead to overproduction/underproduction
  • No dedicated data analyst

Barriers & fears:

  • Fear of overcomplicated graphs
  • Doesn't want to hire anyone to manage analytics
  • Fear of making mistakes with data uploads

How Analytico fits her:

  • Chat-based - like texting someone who knows your business
  • Prediction-focused - tells her what to bake/order tomorrow
  • Simple file upload - uses the Excel/CSV files she already has
  • Clear visuals - charts only when needed, not dashboards full of complex data

Use Cases

Based on the user persona that we created and the insights from our interviews, we thought of the following use cases for Analytico:

Use Case 1: Uploading Excel and Receiving Instant Insights

Actor: Maria ( small business owner)
Goal: Transform Excel sales file into clear dashboards

Steps:

  1. Mihai logs into Analytico
  2. Clicks "Upload Excel/CSV"
  3. Chooses his sales file
  4. System automatically detects columns (date, product, quantity, revenue, etc.)
  5. Shows preview
  6. Mihai clicks "Generate Report"
  7. Within seconds, the dashboard appears with: best-selling products, worst-selling products, peak hours, loss estimation, forecast for tomorrow.

Success Criteria:

  • User understands insights without explanation
  • No technical knowledge required

Use Case 2: Sugesting Tomorrow’s Stock

Goal: Predict demand to reduce leftover products

Steps:

  1. User uploads Excel with previous 3–30 days of sales
  2. Analytico shows: predicted sales for each product tomorrow, recommended stock quantities, risk of leftover.
  3. User prints or downloads the recommendation sheet.
  4. It will be used for next day preparation.

Success Criteria:

  • Reduced waste