Thursday, February 5, 2015

Kony gives enterprises the means to make mobile development a force multiplier for business productivity

Orlando, Fla. -- Kony, Inc. burnished its mobile development credentials this week at the Kony World conference here, detailing new updates to its visual tools and platform, expanding its partner ecosystem, and launching a new enterprise mobile app marketplace with the debut of CRM app Kony Sales.

The combined efforts are designed to help businesses gain enterprise-grade mobile productivity fast, leveraging central services and automation, embracing all end-points from a common code base, and encouraging users themselves to tweak their apps best.

"We are going to do to mobile what Salesforce did to web apps with Force,” said Kony CEO Tom Hogan at the Orlando conference, one of three Kony user gatherings set for 2015, with the others soon in Frankfurt and Dubai.
We are going to do to mobile what Salesforce did to web apps with Force

Hogan encouraged enterprise IT leaders to not force their users to make compromises as they seek mobile apps for extending and improving their business processes. Enterprise business users want to have their native interface usability benefits, but developers need to enjoy cross-platform benefits to deliver their apps with speed and security. They can both get their way, says Hogan. [Disclosure: Kony is a sponsor of BriefingsDirect podcasts.]

 "Consumers won’t tolerate the pace of enterprise IT,” said Hogan, pointing out that demand for mobility has led IDC to predict that 25 percent of IT budgets by 2017 will go to supporting the mobile enterprise.

Trouble in mobile pursuits

At the same time, says IDC, 50 percent of enterprises are having trouble linking mobile front ends to the rest of IT. This is where Kony is focusing its efforts, to bridge the divide between what users demand and enterprises can responsibly deliver in enterprise mobility.

Competitive pressures are trumping IT efficiency, forcing a higher pace and larger budgets to attain effective mobility, says Hogan. A leading mobility analyst agrees.

"We are at the end of the golden age of the standalone app," Forrester Principal Analyst Jeffrey Hammond told the Kony user crowd. “Instead, we’re now in a mobile mind shift, with the vast majority of users already on mobile devices,” he said.

Forrester surveys show that "improving customer experience” in using mobile apps is now much higher among the very top of planned business initiatives, says Hammond.

Factoring "effectiveness, ease, and emotion" are keys to designing good mobile apps, he continued, adding that business should "own an equal share of determining a mobile strategy. … By doing this, you actually help IT get the job done better,” says Hammond.

A big hold-up for mobile apps velocity, however, is the need to code each of multiple end-point platforms, says Hammond. Continuous delivery and fast feedback via analytics is only just beginning but is essential for mobile apps development in-house at enterprises.

To do rapid test and release mobile app dev -- and to gain that feedback loop -- enterprises need force multipliers like stronger tools and platforms with automation, says Hammond. They also need to gain more of the skills needed for a mobile-first capability.

"Kony MobileFabric is a good example of the kind or architecture enterprises need to do proper mobile development," says Hammond.

That's behind the Kony drive to expand its role in a lifecycle approach to enterprise mobile attainment, as the company announced a growing ecosystem of partners that are offering new “ready to run” applications via Kony’s cloud-based business mobile app marketplace.

The Kony Marketplace offers a collection of ready to run apps, reusable components, and design templates. These allow the growing list of partners to speed the process of adopting and delivering mobile apps to meet business demand.

The new partners, who will offer their solutions throught the marketplace include: Broadstrokes, Factual, InfoStretch, Knack, PopcornApps, Quinscape, Redora, Softechnologies, Splyt, Stefinini, UST Global, VeraSynth, and ZineOne.

“Industry experts are predicting that the demand for mobile apps will dramatically increase for enterprise organizations in the next few years,” said Burley Kawasaki, Kony senior vice president of products. “To meet this demand, enterprises are looking for ways to empower their businesses to rapidly deliver secure, enterprise-level mobile apps with great user experiences. Our goal is to provide a rich collection of pre-built apps and app models through the Kony Marketplace, which they can use to quickly build their mobile apps."

Mobile apps are way different

And these new mobile apps need to be designed differently, because they are different. They are typically situational, with dynamic requirements, in high demand, possibly throw-away, and often like consumer apps, said Van Baker, Gartner vice president and leading mobility analyst, to the Kony World crowd on Thursday.

User experience is the key, echoed Baker for other speakers at the conference. "User centricity is the only option. It must bring the relevant information to the user in a relevant fashion,” he said. And so mobile technology needs to adapt to people, not the other way around, he says.

And today’s mobile apps are just a stepping stone. By 2017, 50 percent of today’s deployed mobile apps will be rewritten or replaced, said Baker.

Traditional IT is being shunted aside by those who will get their mobile apps one way or another. Indeed, shadow IT spending is going to 50 percent, and so will be the third largest IT budget item, said Baker.
By 2017, 50 percent of today’s deployed mobile apps will be rewritten or replaced

So IT needs to deliver tools to the enterprise that business analysts can use to make mobile apps, IT will not keep up using waterfall-style code-based development, says Baker. So IT will end up surrendering the client development to business analysts using visual tools, concludes Gartner’s Baker

Other predictions from Baker: By 2018, more than half of all business to employee mobile apps will be created by business analysts with codeless tools like Kony’s. And by 2020, web- and mobile-style app integration will have fully displaced traditional approaches, he said.

That jibes well with what researcher IDC has predicted, that the number of apps optimized for mobility will quadruple by 2016.

Given this sea-change in the enterprise, Kony has moved quickly to help businesses provide mobile-first apps for their sales teams. Kony this week released its first ready to run Kony Sales app suite, featured in the new Kony Marketplace. The mobile productivity extension app for SAP and Salesforce allows sales representatives to:
  • Increase sales rep productivity
  • Manage tasks and follow-ups
  • Accelerate pipeline activity
  • Manage leads, accounts, opportunities and contacts, and
  • Work offline to capture information while traveling, and then sync it to the back-end once they return to the office. 
Built on top of Kony’s Mobility Platform and composed with Kony Modeler, the Kony Sales app can be easily extended, configured and customized by business analysts and sales operations personnel. Kony Sales is optimized for iOS and Android phones and tablets, and has the ability to receive upgrades while preserving customizations.

Expect more business-centric apps like Kony Sales soon, targetng such arenas as finance and healthcare. Kony's ISV partners will help drive the creation of these market-driven apps, said Kony officials.

Composition tool set

Also available this week is Kony Modeler, a powerful visual, composition toolset for business users to assemble and configure mobile-first apps from reusable, lightweight app models available in Kony’s app marketplace. With Kony Modeler business users can rapidly customize their apps for unique industry requirements, business units and processes, and then immediately deploy the changes to end-users on iOS or Android phones and tablets.

Powered by Kony MobileFabric, the enterprise mobile back-end services platform, has also been extended with the addition of a brand new App Services layer that enables IT to power these model-driven applications and allows them to be configured and deployed to the cloud. It enables rapid customization, automatic upgrades and versioning, and significantly lower total cost of ownership (TCO) for ongoing app maintenance.
Enterprises are looking for ways to empower their businesses to rapidly deliver secure, enterprise-level mobile apps with great user experiences.

"We are really excited about our partnership with Kony and our presence in the Kony Marketplace," said Debjani Deb, CEO and co-founder of ZineOne, a real-time mobile messaging platform. "Our solution helps businesses increase conversions on mobile by instrumenting their app with our light-weight, easy-to-use SDK. This enables them to actually have real-time conversations with their customers within the app itself to enhance experience and increase engagement."

“Knack Systems is happy to partner with Kony to bring enterprise mobility solution to its customers. Organizations currently using SAP solutions will be able to quickly empower their mobile workforce by leveraging Kony’s flexible mobile platform and solutions fully integrated with their SAP ERP and CRM solutions,” said George Kaadi, Managing Director Client Services and CIO Advisory, Knack Systems.  “Knack Systems is a niche consulting firm with experience in SAP and Kony technologies that helps customers to enable their mobile workforce to be more efficient and provide better customer experience.”

As enterprises adopt more of a strategic approach to mobility, they change the way they do business, not just attach new front ends to business services, says Forrester's Hammond.

Developers that bring the most context to the mobile app and associated processes wins, said Hammond at Kony World. Think mobile-first, but make sure it’s part of a true enterprises mobility strategy, including the inout from both IT and business, he said.

Looking to the future, Kony expects even more end-points to enter the picture -- from wearables and the Internet of Things -- and need to be addressed with a rapid app development capability. Forrester agrees.

"Expect with wearables a shift from mobile moments to micro moments to hold a user’s attention," says Hammond.

Yet even as the complexity around mobility increases, enterprises are still confronted with the need to get their essential mobile apps to market faster, to modernize their mobile apps lifecycle, and to gain and embed the ability to constantly revise and adjust mobile apps amid myriad back-end services and APIs.

It's into this opportunity that Kony is focused and building global momentum, said Hogan in summing up the conference.

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Tuesday, February 3, 2015

Rapid matching of consumer inferences to ads serves up a big data success story

The next BriefingsDirect big data innovation success story uncovers how New York-based adMarketplace, a search syndication advertising network, uses big data to improve its search advertising capabilities.

In part two of our series on adMarketplace, we'll explore how they instantly capture and analyze massive data to allow for efficient real-time bidding for traffic sources for online advertising. And we'll hear how the data-analysis infrastructure also delivers rapid cost-per-click insights to advertisers.

 Listen to the podcast. Find it on iTunes. Read a full transcript or download a copy.

To learn how, BriefingsDirect sat down with Raj Yakkali, Director of Data Infrastructure at adMarketplace, at the recent HP Big Data 2014 Conference in Boston. The discussion is moderated by me, Dana Gardner, Principal Analyst at Interarbor Solutions.

Here are some excerpts:

Gardner: Tell us about adMarketplace. What do you do, and why is big data such a big part of that?

Yakkali: adMarketplace is a leading advertising platform for search intent. We provide the advertisers with the consumer space where they can project their ads. The benefit of the adMarketplace comes into play where we provide a data platform that can match those ads with the right user intent.

When user searches for a certain keyword, they're directly telling us what they want to see, and we match it perfectly well with our ads. The relationship that we have with our advertisers is that we match them well and make it accessible in exactly what the user is thinking. We do some predictive analytics on top of what the user is saying. We add that dimension to our user search and provide ads aptly.

Gardner: I'm all for getting better ads based on lot of things I already get. Do you have more than just keywords in terms of how you can draw inference, and what sort of scale of data are we talking about when it comes to all that inference information about an intent on behalf of the consumer?

15 dimensions

Yakkali: Keyword search is one side or one dimension of the user search. There are also category campaigns that the advertisers are running. At the same time, there's a geospatial analysis to it as well. There are 15 dimensions that we go through to provide an ad that is perfectly fit for the advertiser and for the consumer to see and take advantage of to meet their needs. With some of the ads, we are trying to serve the user’s requirements and needs. With all these variables, this sounds like you're going to be gathering an awful lot of information. You also need to reply back with your results very fast or you lose the opportunity for that consumer to get the ad and then even click through and make a decision. Tell me about scale and speed.

Yakkali: You're right on with that question. In this business, latency is your enemy. If you look into the certain metrics, there are almost a half a billion requests that we're receiving every day and we have to match all of those ads with a sub-second performance. We have internal proprietary datasets, which we take care of before matching these ads. And there are two platforms that we've built internally.
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One is called Bid Smart. That performs the analysis between the user intent and the traffic sources that the user search is coming from. At the same time, the price of that ad goes to the publisher. There are the pricing strategies, the traffic sources, and the user intent of the search. All of these things are put together. That predictive analytics system gathers all this information and emits the right ad towards the consumer.
With the partnership with Vertica, we’re able to take the dataset, derive analytics about it, and provide our marketers with all that information.

On top of it, if you look into the amount of data, those half a billion requests that are coming into our system, it generates around two terabytes per hour. At certain times, we can't store all of it for analytics. There is a lot of data that's not inside the database. Now, with the partnership with Vertica, we’re able to take the dataset, derive analytics about it, and provide our marketers with all that information. Bid Smart is the one that does the pricing and matching.

The other thing is Advertiser 3D, which provides that detailed analytics into all these dimensions on the metrics. That provides a very good insight. Now, when it comes to the competition or the opportunity to deliver the right ad at the right time, that's where data work flows make a difference.

We utilize Vertica to directly stream all this click data into it, rather than going into certain other locations and then doing it in a batch format. We directly live-stream that data into Vertica, so that it is readily available for analytics. Our Bid Smart System makes use of that dataset. That's where we get the opportunity to deliver much better ads, with price tags, and the right user intent matched.

Gardner: It sounds very complex. There's an awful lot going on for just serving up an ad. I suppose people don’t appreciate that, but the economics here are very compelling, the more refined and appropriate an ad can be, the more likely the consumer is to buy, but there are a lot of resources that don't get wasted in the meantime. Do you have any sense of what the payoff is, either in business, financial, or technical terms for when you can really accomplish this goal of targeted advertising?

Conversion rate

Yakkali: So our conversion rate is a major key performance indicator (KPI) when it comes to understanding how well we are doing. When we see higher conversion rates, that gives us the sense that we've done the best job and user is happy with what they are searching and what they are getting.

At the at the same time, the publishers, as well as the advertisers, are happy, because the user is coming to us again and again to get that similar, beautiful experience. The advertisers are able to sell more products that meet the needs of the user. And the users are able to get the product that really caters to their needs. We're in the middle of all these things, trying provide the facilitation to the advertisers, as well as the users and the publishers' space.

Gardner: I daresay this is the very future of advertising. Now for you to accomplish these goals and create those positive KPIs, are you housing Vertica in your own data center, do you use cloud, hybrid cloud? Given that you have different platforms, different datasets, how do you manage this technically?

Yakkali: On that end, we started with testing cloud two or three years ago, but again, it turned out that because of so many unknowns and troubleshooting, we had to go with our data centers. Now, we host all our systems in our own data centers and we manage it.

We have our own hardware to deal with. Our system is a 24/7, and we have to be able to deliver the sub-second latency performance. Having your own infrastructure, you have the controlled environment where you can tweak and tune your system to get the best performance out of it.
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Considering that it is a 24/7, there are fewer excuses that you can get away with in not delivering it. For that, we do innovation in terms the data flows and the process of how we ingest the data, how we process the data, how we emit the data, and how we clean up the data when we don’t really need it.

All these things have to come together, and it really helps us having that control on all of our infrastructure and all elements in the data pipeline, starting from the user intent and user search, until we provide the data and the results.

Gardner: How long have you been using Vertica in this regard and how did you go about making that decision?

Yakkali: We've been using Vertica for four to five years and our data pipeline was not on Vertica to start with, but as Vertica came into the picture and we saw the great beauty and the powerful features that it brings to capitalize our ability.

That really helped us. With Vertica in place, we have been migrating our mechanics slowly to use it for the real-time analysis and real-time bidding and all those beautiful features that make us do what we can do better. So it’s been a great partnership with Vertica and we see many more features coming in with the new version. Our Bid Smart mechanism is also improving, and with that, algorithmic capabilities are increasing. So it’s progressing.

Feedback loop

Gardner: Tell us a little bit about where your business is heading. In addition to speed, complexity, and scale, where do you see the ability to create this feedback loop? It’s very rapid feedback loop between a lot of incoming data and an action like streaming up an ad. It seems like this could be applied to either other marketing or advertising chores or perhaps even have an ancillary business-development direction. You’ve got this platform and these data centers. Is there something else that you're gearing up for?

Yakkali: At this point, we're in the business of connecting the advertisers, the publishers, and the users. But that is an untapped business to what it can accomplish. The market has started its pathway towards the level of reaching that epitome. If we take a step back and try to understand it, initially, when search started, there was no Google or anything. It was more about curated search.

So the publishers put out all this content together and then projected it out to the user. They didn't know what user wanted. At the same time, when the user looked at this content, they didn't know whether they want it or whether it catered to their needs.

Then, Google came along and user search started. What that directly told was "I want this piece of information. I want to use this piece of information. And I want to see this ad that is relevant to my needs." That’s a very powerful thing. When you hear that part, you're able to analyze that piece and match it properly with the advertisers. But then again, it started to fragment.
At this point, we're in the business of connecting the advertisers, the publishers, and the users.

Now, it’s not only Google. There is Yahoo, Bing, there is mobile, and there are certain apps. There are many apps in the mobile space and each one has its own search. So not all the searches are going to Google, Yahoo, or Bing. Search is already fragmented.

We tap all those pieces. The market that is beyond Google. Yahoo-Bing is stronger and it is growing. So there is a lot of market that needs to be tapped into. We come into the place connecting the advertisers to tap that untapped marketplace.

We've been improving our internal Bid Smart algorithm that came out in the last year. Then, we also launched Advertiser 3D last year as well. Those two products have been providing tremendous growth in our revenue, and the retention rates have been stellar.

The top 60 percent of Google’s top spenders are working with us to complement their business. At the same time, we're also able to provide 50 percent increase in year-over-year revenues. It's additional revenue for them, and even our revenues are increasing based on that fact.

Gardner: It seems like you have an awful lot of runway ahead of you in terms of where search could be applied, and analytics can be drawn from that to augment these services and explode that market.

Is Vertica being used just for the intercept between the incoming data and the outgoing ad, or you are also analyzing what goes on within these marketplace so that you better appreciate, whether you can offer reports, audit trails, and that sort of thing? Is this an inclusive platform, or do you use different analytics platforms for different aspects of what you are doing?

End to end

Yakkali: We do almost everything. It is an end-to-end platform. As part of the business we look into the operational metrics of the whole thing, starting from the user search until the ad is delivered. Then, from that end, there is always that analytics piece that comes onto play, which provides insights to the marketers.

Our market base is filled with the very data-savvy marketers, and they look into each and every data dimension to understand their return on investment (ROI). We give them transparency through our Advertise 3D System and utilizing that, they're able to navigate through the space and aptly tune their campaigns to get the best out of it and to deliver the best to the customer.

Gardner: Any thoughts about other organizations that are also facing significant challenges around speed, scale, also perhaps with a big runway, in terms of knowing that more and more business could be coming their way therefore more data? What would you advise them in terms of the data architecture or the planning in order to accomplish the goals?

Yakkali: When we look at the industries and the market, the ad industry still is untapped. The healthcare industry is just getting into the business of doing much more with analytics. It’s all about the speed and the latency and the insights as well. One, at the operational level and the other, at the insight level to do more innovation on top of it.
Our market base is filled with the very data-savvy marketers, and they look into each and every data dimension to understand their return on investment (ROI).

The ability to listen to the customer depends on how fast you can capture all that feedback, and you tighten that loop of feedback so that you're able to do something with it and make a better product out of it.

So it’s all about taking a look at the datasets very closely as to what they mean, what the user is asking us, what do they want to see, and how you are listening to the customer. Those two aspects really make the difference.

You want to listen to the customer, what they really want. Are you providing it and are you able to guess what they want for tomorrow for that predictive, and going into prescriptive analytics, phase later on. You're telling them what they need to do even before they tell you.

That's the stage that the market is going towards. We're not even scratching the surface of prescriptive analytics. The wave has not yet started towards that route. We're still at the predictive analytics phase, and there is still a lot more to go within that space. Get the foundation stronger, drive towards prescriptive analytics, and listening to your customer, are the three aspects that would make any industry. Those three would be the key foundational pieces for making innovation.

Listen to the podcast. Find it on iTunes. Read a full transcript or download a copy. Sponsor: HP.

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