What 2,500+ logs are teaching us about Food Journal 🌱
Early beta lessons from Food Journal by SOMOS — and why real user behaviour is shaping our updates.
Hey everyone, Khawar here 👋🏾
Been a while since my last update so here’s the tl;dr of what’s been going on before I get to the main event…
→ I’ve been helping get my folks (and their cats!) ready for their move from Spain to Malaysia. They’re really excited about getting here in early August and I’m now an expert on cat passports and quarantine. Everyone wins.
→ I’m just coming to the end of my Wellness Coaching course with NASM and recently completed mat and reformer pilates teacher training. Not going to lie, it’s been a lot to juggle alongside SOMOS, but it has also given me a lot to bring back into Food Journal and the wider SOMOS wellbeing ecosystem.
→ Having been a supporter of BuildPalestine for a few years, I’ve now joined their Nourishing Hope for Gaza Champions initiative - every few weeks, I’ll be sharing details on locally-led Palestinian solutions and how you can help!
→ I’ve also recently joined the faculty at the School of Radical Imagination where I’ll be teaching a course on sustaining social justice work over time.
→ I’ve been having the most fun working with our beta users to develop Food Journal into a truly contextual companion for people trying to build thoughtful, sustainable dietary habits.
I’ll share more about our new mobile-optimised app and features next week but wanted to share what we’ve been learning first as it’s really helped me double down on the holistic approach we’re taking at Food Journal compared with traditional calorie/macro trackers.
Early data from our first 2500+ Food Journal logs
A quick caveat, I run a small social enterprise so paying users, early data and feedback are always exciting. It’s still worth noting that…
↳ a market leading app like MyFitnessPal has millions of monthly users.
↳ comparatively, I’m looking at early insights from a small dataset, not a formal research study.
That said, even a small dataset like this is only possible when people start to actually use your product.
You learn from their habits, they find gaps in your workflows and spot bugs you hadn’t imagined yet.
Anyone who has built a tech product knows that to get to this stage most definitely isn’t a given so I’m genuinely energised to be here and to be using these learnings to improve Food Journal across the board.
So what have we picked up so far…?
At this stage, I’d group the early learnings into four main areas:
What individual meals are telling us 😋
What the daily check-ins are showing ⚡
What we’re learning about dietary patterns 🥗
Who is using Food Journal so far? 🌍
What individual meals are telling us 😋
When someone logs a meal in Food Journal, they are not only asked what they ate.
They can also add:
how hungry they felt before eating
how full they felt after eating (and also 30 minutes later)
how the meal made them feel
where kind of meal it was (e.g. home-cooked, takeaway etc)
any extra context they want to include
That might sound like a lot, but the point is simple: a meal is not just calories, protein, carbs and fat.
Those numbers can be useful but they don’t tell us whether a meal felt satisfying, whether it fitted the day, whether it was rushed, enjoyable or if it helped someone feel good afterwards.
That‘s why Food Journal asks for a bit more context. Not to make logging feel heavier, but to help users build a clearer picture over time.
So far, the early data is encouraging:
😋 Meals feel good: Tasty is the most common meal feel tag at 36%, followed by Nourishing at 26%. Indulgent and Homely both land around 9%, which feels like a healthy mix of food that is enjoyable, satisfying and realistic.
🧭 Appetite looks broadly well managed: before eating, 54% of users were peckish and 28% were hungry. After eating, 57% felt “just right” and 29% felt full, with only 7% uncomfortably full.
🏠 Home cooking is doing a lot of the work: where users tagged meal source, 76% of meals were home-cooked, with smaller shares for eating out, takeaway, ready-made meals and food cooked by someone else.
I’m really interested in this type of data as it tells us more than the content of a plate. The aim isn’t to judge one meal in isolation, it’s to help users notice what kinds of meals support them, satisfy them and fit the life they are actually living.
What the daily check-ins are showing ⚡
Food Journal isn’t a wearable like WHOOP or Garmin, so it can’t passively know how someone slept, recovered, trained or moved through their day.
That’s where the daily check-in comes in.
Alongside meal logging, users can record things like morning energy, activity, recovery and whether they felt fuelled for the day. The point isn’t to turn Food Journal into a wearable, it’s to give the food data a bit more context.
The early daily data gives us a useful picture:
⚡ Morning energy is mixed: 46% of check-ins are moderate, 31% low and 22% high.
✅ Most users still feel fuelled: 96% of explicit “felt fuelled” responses said yes, across 54 responses (it’s a new feature so it’s a very small sample, but encouraging).
🏋️ Training skews strong: strength training leads the activity logs with 87 sessions, followed by walks/hikes, mobility/rehab, racket sports, yoga/Pilates and cardio.
🚶 The current user base is active: 52% describe themselves as moderately active and 33% as very active, so 85% are at least moderately active.
This additional context is especially useful for individual meal analysis as it helps Food Journal give tailored insights. For example, if the user:
had a poor night’s sleep but has a heavy exercise day → the journal may suggest thinking about higher-carb meals or snacks to support training and steadier energy
wants to lower their cholesterol → the journal may highlight nutrients in the meal that can support heart health, such as fibre, unsaturated fats or plant-based ingredients
has just played sport in hot conditions → the analysis may flag hydration, sodium and replacing fluids after sweating.
The goal here is to make the analysis more useful by understanding the day around the food, not just the food itself.
What we’re learning about dietary patterns 🥗
So what are our users actually eating?
The early data shows a fairly practical pattern: main meals are doing most of the heavy lifting, while top-ups are adding support around them.
💪 Main meals are protein-forward: users average around 31g protein per main meal at roughly 466 kcal, with 48g carbs and 15g fat.
🥗 Vegetarian meals are holding their own: omnivore main meals average around 33g protein, while vegetarian main meals average around 31g. The pescatarian sample is still tiny, so I wouldn’t read much into that yet.
🔬 Top-ups are playing a useful role: snacks and supplements add another ~13g protein across the day. Creatine is the most logged supplement, followed by vitamins, synbiotics, whey protein powder and collagen.
🌾 Fibre is in a decent place, with room to grow: main meals average around 7g fibre, so three main meals would get someone to roughly 21g/day before snacks or extras. That’s a solid base, with room to move closer to the UK guideline of 30g/day.
🌱 Whole foods are showing up regularly: 44% of meals include whole-food ingredients, which tells us something useful beyond the macro numbers.
🐟 Omega-3 foods are coming from meals, not supplements: chia, salmon, flax/flaxseed, tuna, sardines and walnuts are all showing up, with no omega-3 supplement entries so far.
Users can also tap into these insights over weekly, monthly, quarterly and all-time trends i.e they can see how their habits change over time.
Hopefully, that kind of analysis can give people more useful support than calorie and macro estimates alone. It helps them look at the broader pattern: whether protein is showing up consistently, whether fibre is building across the day, whether top-ups are supporting them and whether useful nutrients are coming from actual foods as well as supplements.
Who is using Food Journal so far? 🌍
The current user base is still small, but there’s already a clear shape to it. Most users are active, health-aware and interested in food as part of energy, training, strength and general wellbeing.
That shows up in the profile data:
🎯 Goals skew performance-first: 29% of users selected building strength/muscle as their primary goal, followed by general health at 24% and improving performance/energy at 24%. Fat loss is still part of the picture at 14%, but it’s not the dominant use case so far.
🚶 Users are generally active: 52% describe themselves as moderately active and 33% as very active. That means 85% of users are at least moderately active.
🏋️ Strength training leads the activity logs: across 140 activity logs, strength training makes up 62%, followed by walks/hikes, mobility/rehab, racket sports, yoga/Pilates and cardio.
🍽️ Dietary patterns are mixed: 71% of users are omnivores, with smaller groups of vegetarian, pescatarian and no-specific-pattern users. That mix is helpful because it lets us see how different eating styles show up in the data.
The early community isn’t using the product only to lose weight or hit a calorie target. They’re using it to understand how food fits into active, full lives: training days, busy workdays, low-energy mornings, home-cooked meals, supplements, snacks, social meals and everything around them.
That’s useful confirmation for the product direction.
Food Journal needs to stay flexible enough for different goals and dietary patterns, while giving people enough structure to notice what’s actually supporting them over time.
That’s it for now! Keen to see what these patterns look like when we get to 5,000 logs!
In the meantime, if you’d like to try Food Journal , you can do so here:
And if it feels useful, I’d really appreciate hearing how you find it — this is still early, and your feedback will shape what comes next!
Thanks for being here 🙏🏽
Khawar | Founder @ SOMOS 👋🏽
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