Sample plan: The discount information app, UK (Saas launch in UK)

You will receive a detailed European go-to-market plan tailored to your discount-discovery app, the United Kingdom market, London as the launch city, and the most likely business model.

The plan includes the logic, examples, decisions, and actions you can start this week. Where information is missing, I use clearly labelled hypotheses rather than treating assumptions as facts.

Europe, including the UK, often requires stronger trust signals, localization, pricing clarity, and compliance-aware messaging than founders initially expect.

Executive summary

You are launching a London-first discount discovery application that shows customers up-to-date in-store discounts in their chosen city or area.

The first 90 days should not be a broad consumer app launch. The first priority is to secure a reliable supply of discounts from stores, because without fresh offers the consumer product has no value.

• Assumed model: local two-sided marketplace / software-enabled service, with stores providing discount data and consumers using the app or web page to find offers.
• Core positioning wedge: “Verified, local, up-to-date in-store discounts by area — not random voucher codes or outdated posts”.
• First offer to lead with: a free 90-day “Founding Store” pilot for independent and small-chain stores in one London area, where stores submit weekly discounts and receive visibility to local shoppers.
• Fastest path to first revenue: prove store participation and consumer demand in one area, then convert stores to a paid monthly listing or featured placement package. Do not charge consumers first.

Top 2 channels to start with:

• Founder-led direct outreach to stores, because the supply side must be built manually first.
• Local consumer waitlist/community acquisition in the same area, because store partners need proof that local shoppers care.

Main risk: stores may not consistently send accurate discount information unless the process is extremely simple and they see a clear reason to participate.

Decision checkpoint

• Assumed business model: marketplace / software-enabled service, not pure service and not physical retail.
• Assumed launch geography: city-first, starting with one London area rather than all of London.
• Assumed primary launch focus: conclude agreements with stores so they send discount information in advance.
• Assumed first priority segment: independent and small multi-location retailers in one London area with frequent promotions.
• Assumed first offer: free 90-day Founding Store pilot, then paid listing or featured visibility.
• Assumed first acquisition loop: direct store outreach → store submits discounts → local shoppers join/use → proof shown to more stores.
• Confidence level: medium-high. The brief clearly says the launch focus is store contracts, but the exact revenue model is not yet defined.
• If this assumption is wrong: if the product is meant to be consumer-paid subscription only, the plan would shift heavily toward consumer acquisition, price sensitivity testing, and app retention before B2B partnerships.

Market & category analysis (Europe + chosen country)

Category definition:

• Local discount discovery.
• In-store offer aggregation.
• Deal discovery with verified retailer-supplied data.
• Over time, this can become a local retail traffic platform.

What buyers care about in Europe and the UK

• Accuracy: “Is this discount still available”?
• Local relevance: “Is it near me”?
• Trust: “Is this an actual store offer or clickbait”?
• Simplicity: “Can I check quickly before going shopping”?
• Privacy: “Do I have to give too much data”?
• Clear pricing: if stores pay later, they will want to know exactly what visibility they receive.

UK-specific realities

• London shoppers are used to price comparison, loyalty schemes, voucher sites, and discount alerts.
• Many consumers are sceptical of “exclusive deal” claims unless the source is credible.
• Retailers are busy and will not adopt a complex portal early. Email, WhatsApp, or a very simple form will convert better at the start.
• Pricing should eventually be displayed in GBP, with VAT treatment clear. This plan uses EUR because the brief gives budget in EUR; adapt to GBP for launch.

Three concrete local discovery surfaces

• Where people search: Google Search, Google Maps, “near me” searches, TikTok search for shopping finds, Instagram search.
• Where they compare: voucher/deal platforms, store newsletters, loyalty apps, retailer websites, Google Business Profiles.
• Where trust is transferred: local Facebook groups, Nextdoor, student groups, borough/community pages, store Instagram accounts, local influencers.

Three local trust markers that matter

• Last updated” timestamp on every discount.
• Verified by store” badge or clearly labelled “submitted by store.
• Clear area coverage, for example “Currently covering Camden High Street only” rather than pretending to cover all London.

Three competitor archetypes in the UK

• Mainstream option: large voucher and discount-code platforms. These are broad, often online-first, and not always strong for real-time in-store local offers.
• Specialist option: retailer loyalty apps and individual store newsletters. These are accurate but fragmented across many brands.
• Alternative option: community-led deal sharing on social platforms, local groups, TikTok, and WhatsApp chats. These are fast but inconsistent and not structured.

Local language, pricing, and trust conventions

• Use British English: “shops,” “offers,” “high street,” “postcode,” “favourite stores”.
• Show prices in GBP for UK users and store partners. If quoting to investors or internal planning in EUR, convert consistently.
• Delivery and returns are less relevant if the product is focused on in-store discounts, but shoppers will still expect clear conditions: dates, participating branches, stock limitations, and exclusions.
• Avoid exaggerated claims such as “never miss a deal again” unless the coverage is genuinely comprehensive.

Ideal Customer Profile (ICP) + segmentation

Primary segment

• Who they are: independent retailers and small multi-location stores in one London shopping area, especially fashion, beauty, home, gifts, food speciality, convenience, and lifestyle stores that already run promotions.
• Job to be done: get more local footfall when they have discounts, clearance items, seasonal offers, or quiet trading periods.

Triggers

• Slow weekdays.
• End-of-season stock.
• New product launches.
• Local competition.
• Need to increase footfall without paying high advertising costs.

Barriers and objections

• We are too busy to update another platform.
• Will this actually bring customers?
• We already post on Instagram.
• We do not want to discount our brand too much.
• Who are you, and how many users do you have?

Decision criteria

• Low effort.
• Clear local exposure.
• No long contract at the start.
• Ability to control what is listed.
• Visible proof of shopper interest.

Current alternatives

• Instagram posts and stories.
• Window signage.
• Email lists.
• Loyalty programmes.
• Paid local ads.
• Voucher platforms.

Expected outcome/value and willingness to pay

• Early willingness to pay will be low until proof exists.
• Rough estimate: after proof, small retailers may consider around €49–€149/month per location for basic visibility, and €199–€399/month for featured placements or campaign support. Verify in London and convert to GBP.

Where to reach them

• In-person visits.
• Instagram direct messages.
• Email.
• Google Maps business listings.
• Local business associations.
• Business improvement districts where relevant.
• LinkedIn for small-chain owners or marketing managers.

Secondary segment

• Who they are: London consumers who actively look for local discounts, especially students, young professionals, families, and budget-conscious shoppers.
• Why they matter later: they create demand proof for retailers and eventually become the audience that gives the platform value.
• What changes in messaging or channel choice: consumer messaging should focus on “find nearby in-store offers before you shop,” while store messaging should focus on “turn discounts into footfall”.

Primary segment for the first 90 days: independent and small multi-location retailers in one selected London area.

Secondary segment for later expansion: local discount-seeking consumers in the same area.

Why the secondary segment is not first priority: without store-supplied discount data, consumers will not return. Supply quality must come first.

Product diagnosis & positioning

Problem solved

• Stores need a simple way to promote current discounts locally.
• Shoppers need one place to see fresh in-store offers near them instead of checking many store accounts, websites, and windows.

What makes it different from generic alternatives

• Local and area-based.
• In-store focused.
• Store-verified rather than scraped or user-rumoured.
• Freshness is part of the product, not an afterthought.

Where it could become too broad

• Trying to cover all of London at once.
• Mixing online codes, delivery deals, restaurant deals, groceries, fashion, events, and services from day one.
• Building a full app before proving that stores will submit discounts consistently.

Sharpest positioning wedge for launch

Verified local in-store discounts, updated directly by shops in your area.

Use cases that should lead

• Clearance discounts.
• End-of-season sales.
• Weekday footfall offers.
• Limited-time in-store promotions.
• Student or local resident offers where relevant.

Use cases that should wait

• Online coupon codes.
• National chains at scale.
• Restaurant and hospitality offers.
• Cashback.
• Loyalty wallet functionality.
• Price comparison across all retailers.

Positioning statement

We help London shoppers find verified in-store discounts nearby, while helping local shops turn promotions into measurable footfall.

Three supporting proof points

• Discounts show a “last updated” date.
• Offers are submitted or confirmed by participating stores.
• Launch coverage is deliberately limited to one area so freshness can be maintained.

Primary proof asset to build first

A live “London Area Discount Board” web page showing 20–30 verified offers from participating stores, with timestamps and store names.

Messages to avoid

• All discounts in London” — too broad and likely untrue.
• Guaranteed more customers” — risky unless proven.
• Best deals every day” — generic and hard to substantiate.

Launch focus, offer architecture & conversion logic

Primary launch unit

One London area, one simple discount database, 20–30 participating stores, updated weekly.

Onboarding / activation logic

Stores should not need to download or learn software at the start.

Use a simple form, email, or WhatsApp submission process

• Store name.
• Branch/location.
• Offer description.
• Discount amount.
• Start and end date.
• Any restrictions.
• Image if available.
• The founder manually checks and uploads the offer.

First conversion event

• For stores: agreement to join the 90-day Founding Store pilot and submit at least one discount per week.
• For consumers: sign up for local discount alerts or click “save / view offer” on the live board.

What must be visible first

• Area covered.
• Participating stores.
• Current discounts.
• Last updated date.
• How stores can submit offers.
• Simple consumer call to action: “Get local discount alerts”.

What should be simplified before scale

• Do not build complex store dashboards yet.
• Do not build advanced personalization yet.
• Do not launch multiple cities.
• Do not require consumers to install an app before seeing value.

Primary launch focus

Secure store participation and build a credible live discount feed.

Repeat / retention logic

• Stores continue if they see visibility, clicks, saves, enquiries, or footfall signals.
• Consumers return if discounts are fresh, local, and easy to scan.
• Send a weekly “new discounts near you” email or WhatsApp-style alert, subject to consent rules.

What to test before expanding breadth

• Can you get 20 stores to participate?
• Can at least 10 of them submit updated discounts more than once?
• Do consumers sign up or revisit when the feed is refreshed?
• Do stores accept a paid plan after the free pilot?

Offer, packaging & pricing strategy

Core offer

• For stores: local visibility for current discounts in a verified area-based discount feed.
• For consumers: free access to nearby in-store discounts.

What should be sold first

• Sell stores on a free 90-day Founding Store pilot, not a paid subscription immediately.
• The “payment” you need first is reliable discount data and permission to list the store.

Suggested packaging options

• Free pilot: basic listing, one area, weekly discount updates, no long-term commitment.
• Standard paid listing later: monthly listing with up to a set number of active offers.
• Featured placement later: higher visibility for specific campaigns or time-limited promotions.

What should be delayed

• Consumer paid subscription.
• Store self-serve dashboard.
• Complex bidding, coupons, cashback, or commission model.
• Multi-city pricing.

Pricing logic in words

• Charge stores only once you can show local shopper demand.
• Keep pricing low-friction for small retailers.
• Price by location or campaign, not by complex performance metrics at the start.

Rough EUR price ranges

• Founding Store pilot: €0 for 90 days.
• Basic local listing after pilot: €49–€149/month per location.
• Featured campaign: €99–€299 per campaign.
• Premium local visibility: €199–€399/month for stores with frequent promotions.

These are typical ranges / rough estimates. Verify willingness to pay in London and convert to GBP.

How pricing should be displayed in the UK

• Show GBP prices to UK stores.
• Be clear whether prices include or exclude VAT.
• For business-to-business pricing, UK companies often show “+ VAT” where applicable.
• For consumer-facing pricing, if you ever charge consumers, show the final price clearly.

VAT implications

• Confirm VAT registration requirements with a UK accountant when revenue approaches the UK threshold or if you voluntarily register.
• Do not make tax claims in marketing. Keep invoices and pricing presentation clean.

Whether subscriptions, retainers, or memberships make sense now

• Store subscription: yes, but only after pilot proof.
• Consumer membership: not now.
• Retainers: not necessary unless you offer campaign management for retailers.
• Bundles: later, for multi-location stores.

Introductory structure

Join as a Founding Store: free for 90 days, listed in our local discount feed, submit weekly offers, no long contract.

Repeat / retention-oriented structure

Monthly local visibility plan: keep your current offers in front of nearby shoppers, with simple reporting on views, clicks, and saves.

One thing not to launch yet

A paid consumer subscription before there is dense, fresh, local coverage.

Unit economics explained in practical terms

Most important operating threshold

You need enough active stores in one area for the consumer product to feel useful. A thin database will fail even if the app design is good.

Target contract value

• Early target should be around €49–€149/month per store after the free pilot, with a small number of featured campaigns at €99–€299 each.
• These are typical ranges / rough estimates and must be validated locally.

Target repeat or expansion logic

• Stores should update discounts weekly or at least twice per month.
• Consumers should receive a weekly update and return when new offers appear.
• Expansion should come from one successful area to nearby areas, not from jumping across London.

Healthy margin logic

• Manual operations are acceptable in the first 90 days if they help you learn.
• Healthy economics later require reducing the time spent per store update.
• If one store takes 30–60 minutes per week to manage manually, low monthly fees will not work.

Dangerous signs

• Stores join but do not submit updates.
• Consumers sign up once but do not click or revisit.
• The founder spends too much time chasing each individual discount.
• Stores ask for guaranteed footfall before there is a measurement system.

What matters most economically in the first 90 days

• Number of active participating stores.
• Update consistency.
• Consumer signups in the same area.
• Evidence stores would pay after the pilot.
• Time required to maintain each listing.

Acquisition channels & funnel plan

Main acquisition loop

Founder-led store outreach in one London area.

Supporting acquisition loop

Local consumer waitlist and weekly discount alerts for the same area.

A) Awareness (top of funnel)

Priority channels

• In-person store visits.
• Instagram direct messages and email to local stores.

Concrete tactics

• Build a list of 100 target stores in one area using Google Maps and walking the area.
• Approach owners/managers with a one-page Founding Store pitch.
• Ask for one current discount to list immediately.

Why this matters in the UK

Small retailers are sceptical of cold digital pitches. Local presence and a clear pilot reduce perceived risk.

B) Consideration (middle of funnel)

Priority channels

• Simple landing page.
• One-page PDF or Google Doc pitch.

Concrete tactics

• Show mockups of the discount board.
• Explain that the pilot is free and requires only one weekly update.
• Use clear examples: “20% off selected items until Sunday,” “student discount Tuesdays,” “clearance rail this week”.

Why this matters in the UK

Retailers need to see that this is practical, local, and not another vague marketing platform.

C) Conversion (bottom of funnel)

Priority channels

Direct follow-up by email, phone, Instagram, or in person.

Concrete tactics

• Ask for a simple yes: “Can we list your current offer this week”?
• Use a short permission form.
• Confirm listing details and update date.

Why this matters in the UK

A low-commitment first step is more credible than asking for a subscription before proof exists.

D) Retention & referral

Priority channels

• Weekly store update reminders.
• Basic performance summary.

Concrete tactics

• Send stores a weekly prompt: “Any new offer for this week”?
• Share simple metrics: views, clicks, saves, email clicks, or enquiries.
• Ask participating stores to introduce one neighbouring store.

Why this matters in the UK

Local retail networks can transfer trust faster than ads if the first stores have a good experience.

Not now

• Paid Meta or TikTok ads at scale.
• App store optimisation before the web experience proves demand.
• Influencer campaigns with fees.
• Search engine optimisation as the main growth driver.
• National PR.

Single most important acquisition test for the first 14 days

Can you get 10 stores in one London area to agree to list one current discount?

Single most important supporting test for the next 14 days

Can you get 100 local consumers to join a discount alert list for that same area?

Messaging & communication strategy

Primary segment: stores

Tone and style:

• Practical, local, low-risk, not hype-driven.
• Emphasise footfall, visibility, and ease.

Key messages:

List your current discounts where local shoppers can find them.

• Objection it solves: “Why should we use another platform”?
• Buying moment: first outreach and pitch.
• Touchpoint: store pitch page, email, flyer.
• Avoid: “We will transform your sales”.

Free for Founding Stores during the first 90 days.

• Objection it solves: “Will this cost me before I see results”?
• Buying moment: conversion follow-up.
• Touchpoint: direct message, permission form, landing page.
• Avoid: “No risk forever”.

Send us your offer once a week — we handle the listing.

• Objection it solves: “We do not have time”.
• Buying moment: onboarding.
• Touchpoint: onboarding email, WhatsApp prompt, store form.
• Avoid: “Fully automated” if it is manual.

Secondary segment: consumers

Tone and style:

• Useful, local, direct.
• Avoid sounding like a spammy voucher site.

Key messages:

• See fresh in-store discounts near you before you go shopping.
• Follow your area and get weekly local offers.
• Verified offers from participating shops.

Three example headlines

• Find verified in-store discounts near you.
• Local shop offers, updated weekly.
• A simpler way to see what is on sale in your area.

Three ad/landing phrases

• Starting in selected London areas.
• Offers submitted by participating stores.
• Join the local discount alert list.

Three proof elements

• Last updated” timestamp on every offer.
• Store logo/name and location.
• Number of participating stores in the area, once real.

Landing page / presence / conversion structure

Main conversion surface

A simple online landing page plus live discount board. Build this before a full app if budget is limited.

Hero section:

• Clear headline: “Verified in-store discounts in [Area], updated weekly”.
• Subtext: “Follow local offers from participating shops before you go shopping”.

Two calls to action

• Get local discount alerts.
• List your store’s discounts.

Trust section:

• Explain how offers are added.
• Show “verified by store” or “submitted by store”.
• Show “last updated”.
• State current coverage honestly.

Offer structure:

• Consumer side: free browsing and alert signup.
• Store side: free Founding Store pilot with simple weekly submission.

Social proof / trust signals:

• Participating store names.
• Store photos if approved.
• Short retailer quotes once available.
• Local area specificity.

Frequently asked questions:

For consumers

• Are these offers online or in-store?
• How often are they updated?
• Do I need to pay?
• Which areas are covered?

For stores

• Is the pilot free?
• How do we submit offers?
• Can we remove or change an offer?
• What happens after 90 days?

Call to action:

• Consumers: “Join alerts for [Area]”.
• Stores: “Become a Founding Store”.

Lead capture:

• Consumer: email and postcode/area preference.
• Store: store name, contact name, location, current offer, permission to list.

Above the fold

• What it is.
• Where it works.
• Current offer examples.
• Two clear calls to action.

Delay until later

• Full app download push.
• User accounts.
• Complex filtering.
• Personalised recommendations.
• Paid subscriptions.

Content & creatives plan

What to publish

• Current local discounts.
• New this week in [Area]” posts.
• Short store spotlights.
• Simple shopper guides by area.
• Behind-the-scenes proof that stores are participating.

Formats that fit the UK and budget

• Instagram Reels / TikTok short videos.
• Instagram carousels.
• Google Business-style local posts if relevant later.
• Email newsletter.
• Simple flyers or QR cards for participating stores.

What should be filmed / designed / written first

• 10 short videos walking past participating stores and showing the offer.
• 1 one-page store pitch.
• 1 landing page.
• 1 weekly email template.
• 1 simple “Founding Store” badge or window sticker.

Practical content themes:

• This week’s discounts in [Area].
• 3 shops with offers near [Street/Station].
• Student-friendly local discounts.
• Weekend shopping deals in [Area].
• Clearance and end-of-season finds.

4-week starter content plan

• Week 1: publish the concept, recruit founding stores, show the first 5–10 offers.
• Week 2: post “new offers this week,” introduce 3 stores, collect consumer signups.
• Week 3: show before/after update proof: “Updated today,” “Ends Sunday,” “New this week”.
• Week 4: publish a local roundup and ask followers which store categories they want next.

Simple assets the founder can produce quickly

• Phone videos outside stores.
• Screenshots of the live discount board.
• Store quote cards.
• QR code flyers.
• Weekly email with 5–10 offers.

Nice to have later

• Professional video production.
• Influencer partnerships.
• Full brand campaign.
• Animated app demos.
• Long-form search engine optimisation content.

Measurement, analytics & attribution

Practical key performance indicators

• Number of stores contacted.
• Store response rate.
• Number of stores agreeing to participate.
• Number of active discounts listed.
• Number of stores submitting a second update.
• Consumer email signups.
• Offer views/clicks/saves.
• Weekly returning users.
• Number of stores willing to discuss paid plans.

What to track from day one

• Source of each store lead.
• Date contacted.
• Response status.
• Offers submitted.
• Last update date.
• Consumer signup source.
• Consumer area preference.

Simple tracking plan

• Use a spreadsheet or Airtable for store pipeline.
• Use simple website analytics with consent-aware setup.
• Use email platform analytics for open and click data.
• Use unique links or UTM parameters for channels.

UTM naming convention

• utm_source=instagram / email / flyer / directoutreach
• utm_medium=social / email / qr / founder
• utm_campaign=camden_founder_store_pilot
• utm_content=store_pitch / weekly_offers / qr_window

Minimum viable attribution logic

• Do not chase perfect attribution.
• Track whether each store came from in-person, email, Instagram, referral, or local group.
• Track whether each consumer came from social, QR code, referral, or search.

Weekly scorecard should include

• Stores contacted.
• Stores signed.
• Active offers.
• Offers updated this week.
• Consumer signups.
• Consumer clicks/views.
• Store follow-ups due.
• Paid interest signals.

Privacy / consent notes

• The UK uses UK General Data Protection Regulation (UK GDPR) and Privacy and Electronic Communications Regulations (PECR).
• Use clear consent for email alerts.
• Do not add consumers to marketing lists without permission.
• Provide unsubscribe options.
• Use cookie consent where required if tracking beyond strictly necessary analytics.

Postpone

• Advanced attribution software.
• Complex event tracking.
• Predictive lifetime value modelling.
• Multi-touch attribution.

Do not overbuild

• A data warehouse.
• App analytics stack before product-market fit.
• Complex dashboards no one uses weekly.

Risks, compliance & advertising limitations

Main risks in Europe and the UK

• Outdated or inaccurate discounts.
• Misleading savings claims.
• Using store names/logos without permission.
• Collecting consumer emails without proper consent.
• Sending unsolicited marketing to consumers.
• Overpromising footfall to retailers.

How to reduce these risks

• Get written permission from stores before listing offers.
• Show start date, end date, and conditions.
• Use “submitted by store” or “verified by store” only when true.
• Add “subject to availability” where relevant.
• Give stores an easy way to update or remove offers.
• Keep a timestamp on each offer.

Claim-making caution

• Avoid saying “best,” “biggest,” or “guaranteed” unless you can substantiate it.
• Avoid implying complete London coverage.

Privacy / consent realities

• For consumers, use opt-in consent for email alerts.
• For store outreach, business-to-business cold outreach may be possible under certain conditions, but keep it relevant, clear, and easy to opt out. Check PECR rules before scaling.
• Keep personal data minimal.

Email deliverability basics

• Use a real domain email address.
• Avoid mass sending from a new domain.
• Personalise store outreach.
• Include a clear reason for contacting them.
• Stop contacting people who opt out.

Country-specific checkpoints

• Use UK GDPR and PECR as operating constraints.
• Show GBP pricing to UK users and stores.
• Check VAT treatment with a UK accountant before paid launch.
• Ensure promotion wording follows UK advertising standards expectations around clarity and substantiation.

Safer phrasing alternative

• Risky: “We guarantee more shoppers for your store”.
• Safer: “We help local shoppers discover your current in-store offers”.

14-day validation sprint

Main hypothesis to validate

Local stores will agree to submit current discount information if the process is free, simple, and local.

Supporting hypothesis to validate

Local consumers will sign up to receive discount alerts for one London area.

Exact test to run first:

Choose one area, list 100 relevant stores, contact 50 in the first 7 days through in-person visits, Instagram, and email. Ask each store to join the free Founding Store pilot and submit one current offer.

Encouraging signal:

• 10 stores agree to participate.
• 5 stores submit real offers.
• 50–100 consumers join the local alert list.
• At least 3 stores ask what happens after the free pilot.

Weak signal:

• Fewer than 3 stores agree after 50 contacts.
• Stores say the idea is interesting but refuse to submit offers.
• Consumers do not sign up even when shown real offers.

What to do next

• If encouraging: build the live discount board, continue to 20–30 stores, and start weekly consumer alerts.
• If weak: narrow the store category, improve the pitch, test a different area, or change the store value proposition before building the app.

30 / 60 / 90-day execution plan

Week 1–2:

• Priorities: choose one London area, build the store list, create landing page, create store pitch, contact first 50 stores.
• Experiments: test in-person pitch versus Instagram/email pitch.
• What to measure: response rate, store yes rate, number of offers submitted, consumer signups.
• What to cut if it does not work: long explanations, app-first pitch, broad “all London” messaging.
• Failure signals: stores do not understand the value; no one submits a real offer; consumers do not care without known store names.

Weeks 3–4:

• Priorities: reach 20 participating stores, publish the live board, start weekly local alert email, collect first store feedback.
• Experiments: test “Founding Store” framing versus “free local listing” framing.
• What to measure: offer views, email signups, click-throughs, store update consistency.
• What to cut if it does not work: categories that do not have frequent discounts, stores that need heavy chasing.
• Failure signals: fewer than 10 active offers, no second updates from stores, low consumer engagement.

Days 31–60:

• Priorities: improve freshness, add store referral loop, test simple performance reports for stores, start paid-plan conversations.
• Experiments: test featured placement with 2–3 stores, test QR flyers in participating stores.
• What to measure: repeat store updates, consumer repeat visits, QR signups, paid interest.
• What to cut if it does not work: manual processes that take too much founder time, low-performing content formats.
• Failure signals: stores like the idea but will not pay; consumers sign up but do not return; updates become stale.

Days 61–90:

• Priorities: convert first stores to paid pilot, refine pricing, document the repeatable area launch playbook.
• Experiments: test €49–€149/month equivalent in GBP for basic listing, test one featured campaign package.
• What to measure: paid conversion rate, churn risk, time per store per week, consumer retention.
• What to cut if it does not work: paid packages stores do not understand, over-customised store services.
• Failure signals: no store is willing to pay after proof, manual operations cannot scale, consumer usage depends only on founder promotion.

Not now

• Do not build a full native app before validating store supply and consumer demand with a simple web version.
• Do not launch across all of London in the first 90 days.
• Do not charge consumers before the discount database is dense and fresh.
• Do not spend the €500/month budget on broad paid ads.
• Do not promise guaranteed footfall, guaranteed sales, or complete discount coverage.

Assumptions & Confidence

• I assume the real model is a local two-sided marketplace / software-enabled service, not a pure service business. Confidence: medium-high.
• I assume stores are the first customer to validate because the brief says the priority is contracts with stores. Confidence: high.
• I assume the first consumer product can be a web page or simple database before a full app. Confidence: high given the €500/month budget.
• I assume London launch should start in one area, not the whole city. Confidence: high.
• The single missing input that would most improve the plan is the intended revenue model: stores pay, consumers pay, commission, advertising, or mixed.

Top 5 questions to ask the founder next

• Which London area do you want to launch in first?
• Do you plan to charge stores, consumers, or both?
• What store categories do you want to prioritise first?
• Will discount data be submitted manually, scraped, or integrated with store systems?
• Do you already have any store relationships or consumer audience in London?