If you are an entrepreneur, chances are you already know that startup world is tricky! More so with the app startups. Knowing when to take the next step can be nerve-wracking and doing the due diligence is a very important first step that a lot of entrepreneurs miss out. How do you know if your great idea will disrupt the market, or… blow up in your face?
Well, it can go either way, but there is some groundwork that you can do at a minimal cost (or even free) to validate the ideas before investing your hard-earned real dollars into it. The first thing that you might wanna look for is, yep, competition!
The size and scale of this search will differ from industry to industry. Many apps aim for a niche to claim an untapped market, while others may be perfectly happy brawling it out with a dense space. Busier industries will have active communities writing reports and offering their own public research, potentially giving you a better view over the cliff, so to speak.
For now, we will be focusing on the little guy who needs to know what’s in the fog.
So, how and where do we start the research?
The research stage is usually a three-step process, but as you can imagine, those three steps are not completely straight forward.
Let’s use an example.
Your new app is going to help shoppers determine where they can get the most deals for a specific diet. This will give us, the Diet Name (We’ll go with Taco Diet, because I wish it was real), Deals, Cheap, Cheapest, Best, Weight Loss, Lose Weight, Lose Fat, Skinny, Lose Size, Beach Body, Healthy Nearby, Near Me, New Diet, Diet, 2019 (or relevant year), Android/Apple etc.
Allow me to introduce something that everyone should have in their toolbox: Google Trends
If you have never used it, this is a researching miracle, allowing you to search every bit of data you could need on any term you can think of. Not only that, it gives you related terms, related topics, and generally gives you the insight you may never have even considered. The idea is to come up with as many possible relevant terms as you can: if your customers can find them, you have a competitor. Remember to keep in mind common misspellings. If a simple typo can get you an edge, it’s worth knowing about. If you plan to do Split Testing down the line (Also known as A/B Testing), make sure to follow up on those ideas as well.
We know our audience for this Taco Diet will likely have tried similar products for other diets. So, if for example, someone wanted a version of the Weight Watchers app for the Taco Diet, they might search for this as well. Think like your customer, try to put yourself in their position, and think what they would be looking for.
Note: When we are searching Google, don’t forget quotes around the terms you specifically want to search; otherwise it will merely search by all of the words in any order.
With this done, we should have found at least some of our competition. Now it’s time to do it all over again. Ideally, you would want to make sure you are looking through results others may not even think to go to, such as going 7 or more pages deep in a Google Search. You may just find that your competition exists, but never optimized their web presence.
If you are trying to pursue an idea that involves a smart device or hardware (Internet of Things), there is another step you would want to try before wrapping up this first part. Let’s say we’ve gone through, and found absolutely nothing. How do we know for sure? If you already searched every term you can think of, there’s always the option of searching through public record databases. While this won’t be fast, you may be able to find companies and patents registered under specific names or track down companies with no online presence. Offline businesses are rare these days, and unlikely to be able to complete outside of their local area, if that. It’s very likely that you may not have any effective competition at launch in this case.
The great thing about all of this is that it’s free, or at least mostly free. Researching your competition with a reasonable degree of accuracy is far easier than it’s ever been, and the internet is just chock full of fantastic resources to help out in this regard. Below are a few that may help out for your specific situation.
Now that we know our enemy (so to speak), it’s time to know ourselves!
For this, we will be using the data that we found in the first part of our search to get to know our customers better, as well as creating landing pages that will be used to gauge interest and get our early adopters on board.
Landing pages are simple, and they are going to serve as the funnel for all of the information above. There are many tools out there to make one with no hassle these days. While you can use functionally free options hosting and design options like Wix and WordPress, they are also going to be entirely manual when it comes to funneling your traffic, and also will be absolutely buried in the search results without a custom domain to transfer to. We will ideally use an automated system, such as Airstrip.
Now, this tool is amazing. First off, if you have never made a landing page before, it has the entire template ready to go right as you sign up. All that you need to do is go on and put your product information in there. You assign your pictures, put your logos, and describe your product in a few short blurbs.
From there, all we need to decide is whether this will be a sales page, an information page, or a funnel page. As before, everything is already there; sales pages can put their pricing and links, information seekers can put a questionnaire, and a funnel page can direct your customers to download your new app.
You can even run a split test using this, creating two different variations of a similar landing page, and tracking the results of both for data. This can be crucial in determining which path to take with your product. It should be noted that while using their default domain can still technically be viable, due to comparatively fewer people using this over something like Wix, but a custom domain will usually be needed to get those first page results we’re hoping to nab. Remember that once you are on the first page, you generally will get more and more cemented there as your relevance to your search terms grows through Google’s system.
Asking questions can be hard. Asking good ones may be difficult. Asking wrong questions can leave us sunk. Then what do we put in our questionnaire?
Thank goodness for the internet once again. While questions will vary from project to project, there is a site that can actually set up with already made questionnaires for just about anything out there, and like all of the above, it’s free to use to some extent. Start with industry standards like Surveymonkey or its cool buddy Typeform. You will more than likely find what you need on here. If not, they also have templates and all of the information you could ever need on making a successful questionnaire.
So now we have our Landing Page mostly pieced together, we have out Questionnaire ready to hunt down that sweet, sweet data, and maybe we put a slightly different version out there just to test the waters with some different crowds. Now we need to make sure our pages are using the tags we found to be popular earlier, and we’re ready to launch all of this!
See? It wasn’t that hard, and once you have it all down, you can be out and researching that new project in as little as an afternoon… though maybe spend a bit more time just to be sure
Good Luck, and good searching!
Book a free consultation with our team if you are looking for a technology partner to take your startup to the next level.
The post How to validate your app ideas? appeared first on OCDLAB.
]]>Last night I had a nightmare where an eerie voice was dictating me to press 0 for some weird crap, 1 for something even more bizarre and what not. Yeah, the good old, not-so-Intelligent Voice Response (IVR) systems. The good news is, these IVRs might soon become a thing of the past, as smart voice bots equipped with artificial intelligence (AI) start revolutionizing customer services across various business sectors.
Bots in their various unique avatars, understand natural language and efficiently deliver chat (and voice) services. These contemporary bots are fast, self-learning and are continually getting smarter. While ordering food, making reservations, etc. are the most typical examples, bots can do much more, and with some decent learning data, they can mimic the human conversation to a reasonable accuracy.
I am sure, about everyone out there had this experience at least once in the lifetime. You call a customer service number, most likely, already frustrated with whatever problems you were dealing with at that time. Rather than finding a (semi) considerate human being on the other end, a robotic voice starts directing to choose from a plethora of options. Not exactly a good start, right? To make things worse, you can keep pressing nine, but nothing would change until the spooky robotic Satan had its way with you. Of course, the technology was relevant at some point, and perhaps it still helps organizations to categorize the inbound traffic to a certain degree. However, the inconvenience and frustration it causes to the valuable customers are way beyond that helping factor.
According to a Forbes article, a survey by LivePerson revealed that 53% of Americans spend 10-20 minutes on hold every week whereas 86% of people said that they go on hold every time they call a contact center. Needless to say, the industry could use a more humane solution which would not want you to get inside the phone and smash the machine voice on the other end.
The first-generation commercial bots were developed in the mid-1990s, but have evolved now through the advancement of artificial intelligence (AI), machine learning and higher data processing speeds. These bots are also known as chat bots, smart bots or AI-bots, and can handle repetitive, mundane and time-consuming tasks.
Have you seen FAQ sections on the popular websites? If done right, FAQs could be an invaluable asset for business and services (to reduce the number of support tickets).
It could help to answer a lot of those questions. Of course, that was a human who paid attention and anticipated those questions. In the layman terms, bots could be considered as an advanced version of these FAQs. Throw in some artificial intelligence to a step by step FAQ, and there we have a bot in its minimalistic avatar. Bots understand the natural language conversations and work using a decision tree. Depending on the question, bot answers using a pre-defined sequential flow. This is, of course, a simple example and modern-day bots are way smarter than that. These bots can learn from user responses collected over time. Bigger the data size, brighter the bot. The machine learning plays a huge role here, and while the user sees a smooth-talking bot on the front-end, there is a lot that goes under the hood to make that bot sound so smart.
Organizations utilize machine learning algorithms to develop intuitive interfaces to program dialogues in text mode. Sometimes these do not use AI; instead, they work using rule-based methods. A well-trained chat bot can deliver impressive results ‘just like a real person.’ If open questions are formulated, chat bots provide the answer based on keyword research. Therefore, a chat bot’s ability to interact with a customer is typically restricted to straightforward requests.
A significant part of voice bots is derived from text-based chat bots. The most notable advancement is in Natural Language Understanding (NLU)-capabilities that allow software to match the traits of human speech with relevant actions while extracting the specific objects and figures from speech. New machine learning platform help to improve recognition accuracy and enable computer speech sound much like a human.
Latest voice assistants from Google and Amazon combine both bot and speech technologies. Take Google Assistant, which is a two-way conversational voice-activated device and performs day-to-day tasks like booking an appointment. Amazon Echo, a smart speaker, can provide information on news, sports, daily updates as well as play music by connecting to an intelligent AI-based Alexa voice service.
Then there are voice assistances like Siri and Contana for various smartphones that we use on day to day basis without even realizing that it is also a sophisticated bot.
A 2017 Deloitte study of 450 different contact centers revealed that customer interactions over a voice channel would reduce by 17% by 2019, but, will remain significant at 47%, that is three times higher than chat, web and email, the next largest interaction channels.
It is predicted that implementing self-service, chat bots, voice bots, and automation will not reduce the agent headcounts. Combination of technology and infrastructure is needed to support voice-based services in the contact center. As the competition for automation is higher; today’s IVR systems are undoubtedly going to be replaced with voice bots. If this happens, more agents are required to handle the increasing load of complex tasks.
Nevertheless, bots are becoming common in businesses to provide chat-based services round-the-clock with reduced costs. Statistics from contact center software shows that the average price of customer service via phone is nearly $35 to $50 per interaction, while, the text chat costs are much lesser and is roughly $8 to $10 per session. These chat bots can stay online longer and help customers with necessary information.
IoT focused bots are on the way to revolutionize EAM (Enterprise Asset management), MRO (Maintenance, Repair, and Operations), and FSA (Field Service Automation) markets.
Interestingly, many businesses are revamping their support desks with the new whiff of AI voice-based services. However, there are some challenges before it could become mainstream. For example, integrating traditional telephone systems to voice-bot platforms is not easy. Then there are issues related to data privacy and compliance. With voice bot, outbound calls in the contact center seem to be a better fit as the agenda is known, but, it is hard in case of inbound calls due to the evolution of unknown conversation scenarios.
Things are changing as we speak and several companies are helping reshape the traditional helpdesks. Voca.ai has recently introduced telephone voice bots for financial call centers. IBM also has made a lot of progress in developing simpler bots.
Voice bots are still in the early days for this technology, particularly in contact centers. While these might not replace agents and IVR anytime soon, it is bound to happen with a mix of technology and humans.
The short answer is, it depends. Every business has different operational challenges, and as one size doesn’t fit all, there can’t be a generic answer to this question. Book a free consultation with our bot development experts to find out if a bot is a good fit for your business or you are better off with an old-fashioned contact center or IVR.
The post Can Bots replace call centers and IVR? appeared first on OCDLAB.
]]>Over the past few years, the world of internet connected products has outgrown its loyal group of tech hobbyists looking to automate their homes to an industry that is at the genesis of seismic growth. While the consumer space is where IoT is the most prominent, with products such as connected thermostats and lightbulbs lovingly commanded by everyone’s AI personality – Alexa, it is the B2B sector where industrial IoT (IIOT) is causing major disruptions and breakthroughs. According to Forbes, companies such as GE are predicted to spend upwards of $60 trillion (yes, trillion with a T) in the Industrial IoT (IIOT) sector alone over the next 15 years. The question is, why?
Industrial IoT is bringing tremendous value to businesses as it allows them to build upon existing assets, devices, and data. By tapping into existing sensor data, businesses are provided with rich analytics that are solving problems in logistics, manufacturing, customer service, and the supply chain which were once thought to be impossible.
Lufthansa Airlines is using IoT to aggregate real-time aircraft, airport, and weather sensor data to improve on-time performance and optimize operations. Lufthansa aggregates the data together to provide excellent customer service experiences. American machinery and equipment manufacturer, CAT, is using IoT to collect real-time health and fuel consumption of their products to shift from a “repair after failure” model to a more proactive “replace before failure” model which allows their customers such as farmers to keep their equipment running longer with less costly repairs. This also provides CAT with a critical point of differentiation in a highly competitive industry.
Speaking of farmers, farms in California are also deploying custom IoT platforms that gather data from soil moisture sensors and weather to water more efficiently. This reduces consumption in drought prone areas. When you add in the preventative maintenance savings of other IoT connected farm equipment (from companies such as CAT), you can see how the deployment of IoT within multiple sectors has led analysts and industry experts to make some bold claims such as “IoT is the next biggest thing after the invention of the computer.”
IoT is still in its infancy but has already proven to be a formidable disruptor and is primed to be a catalyst of innovation for years to come. Companies of all sizes have the opportunity to potentially revolutionize the way they conduct their businesses and boast a sizeable advantage in their respective fields. The question is, how will your company take advantage of it?
We want to know how your company is using or planning on using IoT in your business! Send us your stories: hello@ocdlab.co
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