What FieldKo does today: AI-Guided Capture checks a survey photo’s quality on the device. It doesn’t recognize products, read prices, count facings, or check planograms, and its result isn’t saved. FieldKo Atlas makes no automatic image-compliance decisions: a person or your own process decides whether a photo shows compliance.
What Good Looks Like
- Photos are sharp, well lit, and free of glare, so a reviewer can judge them.
- Everyone knows that a photo-quality check isn’t a compliance check.
- Any image recognition tool starts with a narrow task that can be checked against human answers.
- A person stays accountable for decisions the tool informs.
- Tool accuracy is measured by category and revalidated after packaging or model changes.
When to Use It and Common Failure Patterns
Use this page when you plan photo questions, or when someone proposes using AI to judge shelf or display compliance. Common failure patterns:- Treating “Great Shot” as “compliant”. A sharp photo can still show an empty shelf.
- Automating a weak standard. AI can’t fix an unclear scoring rule or an out-of-date product list.
- One photo for everything. Expecting one image to prove stock, price, placement, and campaign conditions at once.
- Trusting the vendor’s accuracy figure. A tool that works on one category or store format can fail on another, or when a promotional pack replaces the usual one.
- Hidden correction work. Reviewers fix so many results that the time saved disappears.
Operating Procedure
Use AI-Guided Capture for Photo Quality
- Ask for photos in survey questions, where AI-Guided Capture is available.
- Coach reps to use Smart Capture (Guided) for evidence photos, and to retake when told.
- Review a sample of photos each week for what they show. See Capture Photo Evidence That Holds Up.
Validate Any Image Recognition Tool Before You Rely on It
If you’re considering a third-party image recognition tool:- Pick a narrow task that a person can check, such as “Is the promotional sign visible?” or “Is this known product on the shelf?”.
- Build a validation set. Pick a representative sample of photos across store formats, lighting, devices, shelf density, packaging, and regions. Have a person record the correct answer for each.
- Measure the tool against it. Track precision (how often a positive result is right), recall (how many true positives it finds), and the cost of each kind of error.
- Match the decision to the confidence. Let the tool surface low-risk suggestions, send uncertain results to a reviewer, and require stronger proof before costly or customer-facing actions.
- Pilot against the human process. Compare time saved, issues correctly found, overrides, rework, and whether more issues get fixed. Include setup and supervision costs.
- Keep a trail. Keep the original photo, the tool’s version, and any correction.
- Revalidate after packaging, category, or model changes.
How to Implement It in FieldKo
AI-Guided Capture
Availability: Built-in, FieldKo Atlas app version 1.0.70.- On a survey question that asks for a photo, the photo box says AI-Guided Capture. Reps choose Smart Capture (Guided), Quick Photo, or Choose from Library. See Take Photos with Smart Camera.
- Smart Capture gives live prompts while the rep frames the shot, such as holding steady and leveling the phone.
- After the photo is taken, the app checks it on the device for blur, brightness, and glare. The check doesn’t need a connection and sends nothing to a server.
- The rep sees Great Shot, Acceptable, or Try Again, with tips to improve.
- It doesn’t identify products, brands, prices, facings, signage, or planogram positions.
- It doesn’t check that the whole shelf or display is in the frame.
- It doesn’t save its quality result to Salesforce. Only the photo is attached.
- It isn’t used for visit, account, or pack-out photos, and there’s no setting to turn it on for them.
Third-Party Image Recognition
Availability: External. FieldKo doesn’t include image recognition. Survey photos are stored in Salesforce, so a third-party tool would read them from there and write any results back through your own integration. See Export FieldKo Data and Photos and Integrate FieldKo with Other Systems. Validate the tool as described above before reports or decisions use its results.Fictional Example
Fictional example: a made-up cereal brand, Maple Ridge Oats, tests a third-party tool on one task: “Is the in-store promotional sign visible?” Reviewers label 200 photos from 4 store formats. The sign is visible in 100 of them.
Precision is 81 ÷ (81 + 9) = 90%. Recall is 81 ÷ 100 = 81%. Most misses come from one store format with strong glare. The team decides the tool can flag likely missing signs for review, but a person checks every “not visible” result before any store is marked noncompliant, and reps in that format are coached to use Smart Capture to reduce glare.
What to Measure
Evidence acceptance needs a manual review process, because the quality result isn’t saved. Tool metrics need your own validation records.
What to Do When It Goes Wrong
Checklist
- Ask for evidence photos in survey questions so AI-Guided Capture applies.
- Tell managers that photo quality isn’t compliance.
- Sample photos each week and record acceptance.
- For any third-party tool, define a narrow task and a validation set.
- Measure precision, recall, and overrides by category.
- Keep a person accountable for decisions the tool informs.
- Revalidate after packaging or model changes.