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Guide Your App Store Optimization

Are you on Mobile App Space and facing difficulty in marketing your app…?

Do you want views on your App among 3 million mobile apps already available?

Do you want your App to come in suggestions when keyword is typed?

Are you facing difficulty in “App Store Optimization”?

In the highly saturated market and on the humongous platform of Google store, Apple store and other App stores, people usually make mistakes in understanding ASO and blindly follow the myths. It’s important to understand the various key-points and methods for marketing your app. On your way of making your apps more visible and grab more app users and then convincing them to download your application. In other words, improving your ASO rankings and deliver more traffic to your app store page, avoid following mistakes:

Myth #1: You Need To Change Your Title Too Often
Reality #1: Pick a title and stick with it.

Avoid frequently changing your app’s title in hopes of improving ASO ranking. Your title is the single most important aspect of app store optimization, but repeatedly changing your title will not help your ranking. In fact, doing this may be detrimental to your ASO. As more and more users begin downloading your app and leaving reviews, your app will naturally move up in the rankings. If you keep changing the title, however, it will be more difficult for users to spread the word about your app. Instead, pick a good ASO title from the start and stick to it.

1. Make it short — 25 characters. 10-productivity-wizard-in-app-store (2)
A short title is one THAT users can read in a single screen. Lengthy titles will get cut off. For the single most important piece of search metadata in the app store, you don’t want it to get chopped.

The app below — Productivity Wizard — only has part of their title featured in the screen. They would be better off not producing such a lengthy title. Because I can’t see it from my app browse screen, I’m less likely to download it.

2.Make it creative.
Why creative? Searchers are either categorical or navigational. A user who has heard of or seen your app will be conducting a navigational search to access it. If this title is creative, it is more likely to be cheap mlb jerseys remembered — and thus to be successfully searched for.
A navigational search is something like “Angry Birds” or “Evernote” as opposed to categorical queries such as “bird game” or “note taking app.”

3. Make it unique.
Lack of unique title means you are going to lost in the crowd is similar to creative, but with a twist. Creativity is something that will stand out to the user. You don’t want your app to get lost in the morass of bandwagon apps like Flappy Pig, Flappy Wings, Flappy Fall, Flappy Hero, Flappy Monster, Flappy Nyan, etc. ad nauseam. Bandwagon apps are rarely as successful as the titan they were following.
A navigational search for a “flappy” app produces 2,193 results. Lack of a unique titles means you’re going to get lost in the crowd.

5-search-for-flappy (2)

Myth #2: Stuff Your Title or Description with “Keywords”
Reality #2: Use a Keyword, but don’t keyword stuff.

Keyword stuffing will negatively affect your ASO just as much as it would affect the SEO of a website. Repetitive use of keywords in a title or description in order to increase ASO won’t help your app move up in the rankings. Your app could actually end up suspended if you attempt to stuff it with keywords. Instead, use keywords naturally throughout your title and description. Again, to reference my point above, don’t stuff it. But use keywords to enhance ASO.

 

App titles that contained keywords had a 10.3% higher ranking than those without it. 10.3% doesn’t sound like a lot. However, if it’s as easy as popping a keyword in the title, why not?

Let’s go back to the data that We surveyed in the beginning. Remember how many users search for apps?

8-app-discovery

 

 

 

 

 

 

 

 

 

Myth#3: It Is All About Downloads & Ratings.
Reality#3: Ratings Are Important, But Not the End All.

Judging from ads and press releases, you might be misled to think that ratings are the key performance indicators you need to track to measure success. Ratings, of course, are a good signal of how customers consider your efforts; the download number is a signal of success. However, then?

Then you need a long-term digital strategy that involves all wholesale nfl jerseys China aspects of app publishing and distribution. Ratings do impact on user’s perception; they do not affect app store rankings. Five stars make a good impression; they do not make your ranking.

The truth is, while app ratings are important, they aren’t as significant as most people think in affecting an app’s rankings.

To uncover the truth behind the impact of rating, Inside Mobile Apps conducted a study. They first examined a random sampling of the easy search terms (1-25 results), medium search terms (26-100 results), and competitive search terms (101+ results) to see how each app ranked based on the ratings, both in iOS and Google Play’s search.
Here is what they came up with for iOS rate/rank comparison:

10-average-rating-by-position-iOS

“Google Play’s search algorithm seems to take a more meritocratic approach to app discovery and visibility, letting higher quality apps rise to the top.”

11-avg-search-rating-by-position-google-play

 

Myth#4: Being On the App Store Is Enough
Reality#4: It Needs a Lot Of Downloads To Get Recognized.

This is a die-hard myth: now that you are on the app store, hidden somewhere, you do not really need other work. Everything will happen as some sort of magic, and downloads will flow as a mere consequence of you being there. Some still believe that as long as your app is there, people will find it. You do not need to advertise it; you do not even need to update it.

The truth is, with millions of apps available, it will take much collateral work to avoid failure. ASO is just one piece of the puzzle, and the competition is so fierce that you will need more ‘traditional’ marketing methods to sell it (from social media marketing to content marketing, advertising and PR).

In above we discussed ratings have a less-powerful impact than we might think. But the impact of downloads is usually underestimated.

It’s a tough deal, because in order to get more downloads, you need more downloads. Let the data speak.

13-how-downloads-correlate-to-search-rankings                                   Apps with more downloads simply rank higher. That’s all.

Download velocity depends a lot on how your app does from a marketing standpoint.

path to popularity:

14-ASO-charts

Myth#5: DESCRIPTION IS NOT THAT IMPORTANT
Reality#5 Description is very important.

When you try to sell something, the first thing you do is to describe the value of your product, the uniqueness of its features. Easy, not? Well, not for many developers that still believe the description is an ‘extra’, not a mandatory element of the app store presence. This is a dangerous myth, and it can kill your efforts, leaving you app into oblivion.

Description is probably the second major element in ASO, right after the title. While not directly linked with rankings, it has a great role in the store algorithm. Don’t try to stuff it with keywords, just focus on the natural incorporation of keywords in what you are describing. Moreover, remember that apps now show up in Google’s result pages too.

 

Mistake #6: Quality Of Your Screenshots Does Not Matter
Reality #6:: Screenshots Play Important Role

Quality Screenshots are equally important for the App Marketing on App Store.

Better UI and high end Picture Quality also convince user to download app and feel the features that has been shown in Screenshots.

Στιγμιότυπο-οθόνης-29

Success in App Store is avoiding these myths and it is what drives potential users to install an app. Think of your app page as a storefront on the busiest boulevards in your area and apply each part of our guide to improve your ASO rankings and deliver more traffic to your app store page.

For Further help and queries, say Hello to us on hello@mantralabsglobal.com

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The Future-Ready Factory: The Power of Predictive Analytics in Manufacturing

In 1989, a missing $0.50 bolt led to the mid-air explosion of United Airlines Flight 232. The smallest oversight in manufacturing can set off a chain reaction of failures. Now, imagine a factory floor where thousands of components must function flawlessly—what happens if one critical part is about to fail but goes unnoticed? Predictive analytics in manufacturing ensures these unseen risks don’t turn into catastrophic failures by providing foresight into potential breakdowns, supply chain risk analytics, and demand fluctuations—allowing manufacturers to act before issues escalate into costly problems.

Industrial predictive analytics involves using data analysis and machine learning in manufacturing to identify patterns and predict future events related to production processes. By combining historical data, machine learning, and statistical models, manufacturers can derive valuable insights that help them take proactive measures before problems arise.

Beyond just improving efficiency, predictive maintenance in manufacturing is the foundation of proactive risk management, helping manufacturers prevent costly downtime, safety hazards, and supply chain disruptions. By leveraging vast amounts of data, predictive analytics enables manufacturers to anticipate machine failures, optimize production schedules, and enhance overall operational resilience.

But here’s the catch, models that predict failures today might not be necessarily effective tomorrow. And that’s where the real challenge begins.

Why Predictive Analytics Models Need Retraining?

Predictive analytics in manufacturing relies on historical data and machine learning to foresee potential failures. However, manufacturing environments are dynamic, machines degrade, processes evolve, supply chains shift, and external forces such as weather and geopolitics play a bigger role than ever before.

Without continuous model retraining, predictive models lose their accuracy. A recent study found that 91% of data-driven manufacturing models degrade over time due to data drift, requiring periodic updates to remain effective. Manufacturers relying on outdated models risk making decisions based on obsolete insights, potentially leading to catastrophic failures.

The key is in retraining models with the right data, data that reflects not just what has happened but what could happen next. This is where integrating external data sources becomes crucial.

Is Integrating External Data Sources Crucial?

Traditional smart manufacturing solutions primarily analyze in-house data: machine performance metrics, maintenance logs, and operational statistics. While valuable, this approach is limited. The real breakthroughs happen when manufacturers incorporate external data sources into their predictive models:

  • Weather Patterns: Extreme weather conditions have caused billions in manufacturing risk management losses. For example, the 2021 Texas power crisis disrupted semiconductor production globally. By integrating weather data, manufacturers can anticipate environmental impacts and adjust operations accordingly.
  • Market Trends: Consumer demand fluctuations impact inventory and supply chains. By leveraging market data, manufacturers can avoid overproduction or stock shortages, optimizing costs and efficiency.
  • Geopolitical Insights: Trade wars, regulatory shifts, and regional conflicts directly impact supply chains. Supply chain risk analytics combined with geopolitical intelligence helps manufacturers foresee disruptions and diversify sourcing strategies proactively.

One such instance is how Mantra Labs helped a telecom company optimize its network by integrating both external and internal data sources. By leveraging external data such as radio site conditions and traffic patterns along with internal performance reports, the company was able to predict future traffic growth and ensure seamless network performance.

The Role of Edge Computing and Real-Time AI

Having the right data is one thing; acting on it in real-time is another. Edge computing in manufacturing processes, data at the source, within the factory floor, eliminating delays and enabling instant decision-making. This is particularly critical for:

  • Hazardous Material Monitoring: Factories dealing with volatile chemicals can detect leaks instantly, preventing disasters.
  • Supply Chain Optimization: Real-time AI can reroute shipments based on live geopolitical updates, avoiding costly delays.
  • Energy Efficiency: Smart grids can dynamically adjust power consumption based on market demand, reducing waste.

Conclusion:

As crucial as predictive analytics is in manufacturing, its true power lies in continuous evolution. A model that predicts failures today might be outdated tomorrow. To stay ahead, manufacturers must adopt a dynamic approach—refining predictive models, integrating external intelligence, and leveraging real-time AI to anticipate and prevent risks before they escalate.

The future of smart manufacturing solutions isn’t just about using predictive analytics—it’s about continuously evolving it. The real question isn’t whether predictive models can help, but whether manufacturers are adapting fast enough to outpace risks in an unpredictable world.

At Mantra Labs, we specialize in building intelligent predictive models that help businesses optimize operations and mitigate risks effectively. From enhancing efficiency to driving innovation, our solutions empower manufacturers to stay ahead of uncertainties. Ready to future-proof your factory? Let’s talk.

In the manufacturing industry, predictive analytics plays an important role, providing predictions on what will happen and how to do things. But then the question is, are these predictions accurate? And if they are, how accurate are these predictions? Does it consider all the factors, or is it obsolete?

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