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[Video Blog] Interview: Chetan talks Growth Marketing with Destination CRM

Chetan Kulkarni, CEO of Vizury was at the New York City office of CRM Magazine to talk about the new wave of personalizaiton in marketing and Vizury Engage, the Growth Marketing Platform custom built for eCommerce, Finance and Travel verticals.

Chetan spoke about the inception of Vizury and how, in the past 8 years, we have evolved into the Growth Marketing Technology company that it is today. Our growth platform, Vizury Engage helps marketers grow digital conversions through user personalization across channels.

The interview was focused on Engage and how it is different from other marketing automation platforms in the industry.

You can watch the interview here:

You can read the full article with excerpts from the interview here.

 

Creating mobile apps that meet customer expectations

This article was orginally published at Chief Marketer – www.chiefmarketer.com/creating-mobile-apps-that-meet-customer-expectations

Though many leading mobile apps have garnered millions of installs worldwide, retaining users remains the key challenge in determining success. In order to survive, mobile apps must combat churn by meeting the consumer’s ever-changing expectations.

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The average mobile user has begun to expect more personalized interactions with brands. This is at the crux of enhanced user engagement and retention rates, and marketers have been exploring various methods to engage and re-engage their app users. Among these, push notifications have proven to be the most powerful, owing to their ability to reach users and their (now) non-intrusive nature as compared with other channels.

Push notifications have gone through several phases of evolution in terms of content format, trigger points, and personalization scale. Each of the four major phases of evolution of the famed push notification has its pros and cons in features, some of which have been completely phased out.

Static push

The static push was fairly primitive, rather like the primate phase of human evolution. It couldn’t stand on its own two feet, but provided a great launching point for future evolution. An app marketer would send a push message—such as “20% off on shades this summer”—to all app users at a particular time of a day. This message sent to the entire user-base was generic, time-based, and completely un-personalized. CTR of such notifications used to be a meager 1% or less, meaning users mostly ignored static push messages.

Segment level personalized push – text format

The next step in the evolution of push was the neanderthal stage. In this phase, user data was integrated to add the “fire” that push notifications needed. Information about app users began to play a critical role in the marketers’ efforts to understand user behavior and customize messaging. Users were segmented based on distinct personas that reflected their in-app behavior. Messaging was then customized for each segment, and an in-app event was defined as the trigger point, such as a product page view, drop off from cart, etc. CTR levels climbed a bit to about 3%, owing to a relatively greater level of customization. The fire created by user data and persona targeting reinvigorated customers looking for engagement.

User level personalized push – with product image

The next stage of evolution brings us to the upright-human equivalent of the push notification, capable of using various tools such as segmentation, which was a level deeper in personalization. Push messaging wasn’t customized to entire segments of user personas any more; instead, it was customized to each individual user. Another significant development on the content front was that, along with text, images could also be included in the push — such as of the product last viewed by each particular user. This product banner would be deep-linked to the product view in the app, and helped marketers connect with more users. CTR thus went up to an average of 8%.

Multiproduct push carousel

The latest iteration of push is likened to modern man, fully capable of accomplishing everything its predecessors could, but adding the ability to anticipate. This is the multi-product carousel. It allows push messages to feature not only the user’s last visited product, but five other recommended products as well. The push is more dynamic, as the user can scroll through the products within the push itself. Machine learning algorithms help marketers determine which five products to recommend based upon a number of parameters.

While it’s tough the say what will come next, it is clear that the mobile app is here to stay. And because of its adaptability, push is one its most compelling engagement tools. Mobile marketing automation platforms are helping app marketers make sense of user data and personalize push for better engagement and eventual transactions.

 

How not to become ‘impersonal’ while being ‘personal’

Am I alone in thinking that, when I receive a “personalized” email from a brand – i.e. it greets me by name, it actually feels pretty impersonal?

To me, “Hi Prasenjit” just means I handed over my personal details to someone and now my name is sitting on their database waiting to be used in marketing communications. But do they really know me? And will they be using my data for something that will be of benefit to me? I’m pretty sure the answer to both of those questions is a ‘no’.

Personalization now means more than calling your customer by their first name. I don’t know whether it’s laziness, or a lack of the right tools, brands today know so much about their customers – so why aren’t they using the data they have to really tailor their messages and make them relevant to the individuals they’re talking to?

Personalization has to be a key priority for marketers in 2016.

Why is it important?

When executed well, personalization, has clear benefits for brands. For example, for a bank, the CTR on a personalized “Next Best Action” recommendation banner on the Home page is thrice the CTR of an equivalent, non-personalized recommendation.

But it’s not always easy to do it right. Personalization is a tricky beast…

For customers, it can be a sensitive – and sometimes contradictory issue. People are very aware that organizations collect data about them and, as a result, have come to expect brands to know their preferences and market to them accordingly. They want brands to be open and honest about what they know and to be helpful in return. They also want confidence that their data is secure.

Get the balance wrong between what you know about your customers and how you use what you know, and customers can be left feeling very suspicious. You can lose their trust, jeopardize business and even appear intrusive if you start using information inappropriately or that customers didn’t know you had.

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True personalization is about really knowing your customers and using what you know to mutual advantage. As marketers we know that a customer’s purchase and transaction history, behavior and preferences can steer us towards offering similar products and services – and that’s absolutely what we should do.

But…

Imagine the power of being able to offer a host of tailored benefits as well – from discounts and offers, to useful information right when they need it and through channels they prefer the most. We’re able to collect more data about our customers now than ever before – but we’ve got to make them want to give it to us and once we’ve got it, we need to use it for their benefit, not just our own. When you know people’s motivations, tendencies and pain points you can really start to personalize what you offer them. And when you start to offer them something relevant that makes their lives easier or better, that’s when the rewards come back to your business. That’s what all marketers are looking for, the power of 1:1 personalization.

 

Meet Vizury at eTail East 2016: We’re at TT4

1500 attendees and over 600 retailers registered, eTail East 2016 is going to be an exciting event this year and we couldn’t miss it. As sponsors at eTail East 2016, we are going to be there at The Sheraton, Boston on August 16 and 17th.

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Vizury at eTail East this year

We have just launched Engage Commerce, the Growth Marketing Platform built for Ecommerce brands and have an exclusive Engage Commerce experience for eTail attendees. We are pretty sure this is the best thing that has happened to online retail, yet.

If you are attending eTail East this year, we’d love to see you. We will be available at TT4 during the time slots given below. Drop by TT4 to have a quick chat on improving user engagement that translate into conversion for your brand or to try Engage Commerce.

  • Tuesday, August 16: 7:00am – 5:00pm
  • Wednesday, August 17: 7:00am – 5:00pm

Here’s how you can find us at TT4.

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And if you are looking for an added incentive, we have a Raffle draw every 4 hours.

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We also have an e-sign up for the first Raffle, click below and sign up now. It might just be your lucky day!

See you at eTail East 2016!

P.S: Don’t forget to catch the 3 omni channel trends at eTail East this year and the complete ECommerce Marketing cheat sheet – must read for all eTail East attendees.

 

Beat the Benchmarks to be an App Marketing Winner

This article by Deepak Abbot was originally published on Growthbug.

Here are some Mobile App benchmarks which you need to keep beating to stay ahead.

Beta the Benchmarks to be a winner Deepak Abbot Vizury

 

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For a complete guide on my daily growth hacks, check my presentation here:

I will be happy to hear your feedback on this. Feel free to comment here or tag me on twitter @deepakabbot or mail me at dabbot@gmail.com

 

First, Second & Third party: The Devil is in the Data

Before we delve deep into this headline, let us briefly understand as to what the above data sources mean:

  1. First Party – Data generated by the self is classified as first-party data. In the context of ad-tech, the data generated by users online belongs to the respective advertisers and are first party data (to be used for themselves). For example, data generated by users while they browse Coverfox belongs to Coverfox and are to be used by Coverfox
  2. Second Party – Data generated by a source but to be exclusively used by another partner is second-party data for the partner buying the data. For example, data generated by Amazingoffer.in if used by Shopclues as part of a specific partnership, then the data is second-party data for Shopclues (which is buying the data as part of strategic tie-up)
  3. Third Party – Data generated by a source, but distributed by an intermediate platform, and is consumed by clients of this platform, is third-party data for the client consuming it. For example, data provided by a partner X and is made available on Vizury platform and is consumed by Vizury clients, is third-party data for Vizury’s platform clients.

The way ad-tech has evolved over the years, value of first party data has been (and continues to be) the most prominent. When a user lands on the website, one gets the perfect chance to understand as to what the user is interested in and then through a series of steps take these users towards the purchase or whatever the end objective is. For example, if a user lands on the Coverfox website means that the user was in some way interested in purchasing some form of an insurance product (Car, Bike, Health, Travel etc.). But for some reason, these portals have only been able to convert a fraction of these visitors into customers.

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What should they do next? This is where the ecosystem evolved and complementary marketing partners evolved to help these portals mine their user data and use it to perfection. Some of the tools available to achieve maximum efficiency are:

  • Call center led conversion (if user dropped a lead)
  • Remarketing (based on first-party data)
  • On-site personalization (for next-visit)
  • On-site recommendation

and many more. These tools or partners did help improve conversion and engaging users more effectively. They tap into all sorts of user footprints, apply all sorts of algorithms (machine learning, deep learning, AI, predictive modeling etc.) and have definitely created an added level of intelligence, thus creating a user experience.

But at times, there is scope to do something more. What if the questions are,

  • Can I know something more about my visitor/user, when they land for the first time
  • Can I influence user basis their external behavior (outside my site)
  • Can I achieve cross-sell, up-sell basis information which is derived from multiple sources

Some of the above questions have resulted into the concept of second & third-party data. If a portal can get into strategic tie-ups wherein the 2 partners are complementing each other, then such data-exchange (in closed private-view) is what is known as second-party data. For example, insurance portals (Coverfox) can tie-up with travel partners (like MakeMyTrip) and reach out to all the users who have purchased flight tickets and sell them travel insurance. Now this can be done either within the context of MakeMyTrip site or outside on display networks as well by leveraging partner platforms like that of Vizury Engage.

Another way is where a platform also can get into generic tie-ups with large data-sellers and humanize the information foot-print into actionable insights. Subsequently overlap these insights with client data and help them deliver relevant messaging. For example, basis 3rd party data if Vizury is able to predict that a user is a heavy traveler, next time this user comes to the Coverfox portal for the first time, s/he can directly be taken to the travel insurance section (and not default homepage). Or if this user is found on a banking site, one can personalize an onsite notification, selling them travel related credit-card. Not just this, intelligent platforms can link data-views to first understand if this user already has a credit card or not, or specifically a travel credit card. Only if the user does not have a travel card, will he be shown a travel credit card, else some other travel up-sell product.

What next? Keep thinking and come up with use-cases which can challenge the contours of digital and traditional marketing. And then seek platforms which can help you execute such use-cases, while helping make data available.

Write to us at marketing@vizury.com with your thoughts on the devil data.

Cohorts to LTV, CAC to MAU: Tips to make marketing meaningful, avoid Vanity

This article was originally published at Yourstoryyourstory.com/2015/10/metrics-vanity/

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We keep hearing about a lot of growth metrics all around us, but ever wondered, if all that ever made sense? Learn what real, meaningful metrics are & use them to drive real growth.

Here are some of the popular terms which can be termed as Vanity if not reported rightly:

Install Base — Barring highlighting the Install buckets milestones (check the note), there is no point in dwelling on the install base as we all know how most Apps are grappling with over 70% uninstall rates. Net Install base any one?

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Active Users — Happy to see that active user is now the widely used metric than awfully flawed Install Base. However, how you define an active is important too. For example a chat app highlighting MAUs is a clear eyewash when companies like Snapchat are taking about HAU (hourly active users). MAU is losing relevance for most apps, so stick to short durations if you really want all of us to believe your great numbers. (Here is a great hack to find MAUs for most apps)

Retained Users — If you spend consistently on acquiring new users which leads to an overall increase in MAUs, it will an incomplete analysis if the overall MAU % is the only metric you track. It can be a bit misleading as you may fail to notice the actual leak in users. A good analytics person will measure the growth of increase in active users minus the new users acquired that month.

Here is a sample illustration on arriving at Retained user’s growth:

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Category Rank — Yet another “How cool we are” metric. It’s useless unless you are visible in Top 25 overall Apps. For example, in India Play Store (as of 30/9/2015):

  • No.1 Sports App = No.206 overall Free
  • No.1 Business App = No.168 overall
  • No.1 Medical App = No.100 overall
  • No.1 in Books & Reference = No.109 overall
  • No.1 Finance App = No.71 overall

So prepared to be judged if you boast about high category rank. Is your app among top 5 sports Apps of India? 😉

Trending Apps — It’s another myth and a favorite flaunting badge for some marketers. It means nothing to appear in trending if you are not in Top 100 overall. For example, in India Play Store, out of top 25 trending apps, only 7 are visible in Top 100 overall free and almost 90% apps never make it to Top 50.

Monthly Retention — Cohorts are often discussed among growth hackers as the definitive way to assess the App’s health. However, it is extremely important to understand what not to quote. For example, Week 8 retention is different from Month 2 retention. Month 2 in all probability will show a much higher retention as it would even count someone who must have visited the app 29 days ago.

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CPI — It’s another term which is quite popular among marketers. I have hardly interviewed any product/business/marketing person who didn’t boast about how they went about optimizing CPIs. Think again — is low CPI a good benchmark? For a news app, it is easy to get installs by showing attractive looking Bollywood pics in its Facebook/Google Ad — will the user acquired by such misleading Ad likely to stay active? So please move to CPaU (Cost Per Active user model).

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Real CAC — Next step after CPaU is to find CAC which sets the basis of any marketing campaign. CAC traditionally is calculated by dividing the total marketing budget by converting users. However, with lucrative discounts being offered to acquire new users, the amount of discount needs to form a part of your acquisition cost to arrive at rCAC

LTV or LNP — Lifetime Value of a User is an important metric to allow a marketer to continue spends as long as CAC < LTV. Real Growth Marketer would go one step extra by measuring Lifetime Net Profit of a user to ascertain if the startup would ever make profits from the users they acquire thru marketing. Below is a dummy illustration to show how Real CAC & LNP Ratios should be calculated:

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CTR or CVR — Marketer loves to boast about CTRs (Click-thru) as it highlights the quality of creative used but did it result in your app download? Banner might be enticing enough to click but not useful enough for someone to download the App. This brings the concept of CVR (Conversion Ratio from Click to Download) — click leading to an app download is the real measure of campaign’s success. Facebook optimizes campaigns based on conversions under oCPM and CVR plays a direct role in lowering CPCs (despite fixed CTRs) thus reducing the Cost Per Install.
Hence a true Growth hacker would focus on increasing CVR for their App campaigns.

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Play Store recently made available a new report which makes calculating CVR much easier.

Qualified Visitor — Lots of Apps rely on push/email/social marketing which can bring in hoards of visitors. Counting all visitors as equal is not advisable. For example, in the image below, how many visitors would you treat as “Qualified” — 23mn or 30mn?

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The real growth hackers are the ones who are true to themselves and don’t cave in to pressure of tweaking the data to make the stakeholders happy. So if you are the one and follow all of the above metrics truthfully, then accept a high five from me. Cheers!

I will be happy to hear your feedback on this. Feel free to comment here or tag me on twitter @deepakabbot or mail me at dabbot@gmail.com

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Stuck with an old school Mobile Push Notifications Platform?

Personalised Push Notifications with Machine Learning on Vizury Engage App

Marketing Automation Tools have always been rule-based. And this trend started with email marketing automation tools. The marketer was expected to know whom to send an email to, what message needs to be sent & the automation tool would send emails to thousands of subscribers. This worked well in the early computing days when value-add meant automating mundane tasks using computers.

The Mobile Marketing Automation landscape today

So much has changed since then. With the advent of Mobile Apps, a major chunk of email marketing got ported over to Mobile Push Notifications. Since Push was presumed to reach users anytime via the mobile, Push automation (sending a Push notification out to thousands of Mobile App users) took prominence in many mobile marketing strategies. These notifications were sent to broad user segments and were not really relevant to every user. And so a whole new category of products called “Mobile Marketing Automation” was born. Companies like MixPanel, MoEngage, Localytics, LeanPlum, Appboy & Kahuna lead the pack as “Poster Boys” today.

So, what went wrong?

But there’s something amiss with all of these tools. This was first felt when marketers saw that 90% of users either ignored or unsubscribed from Push Notifications.

While porting the mass segmentation & mass emailing feature-set to Mobile Push Notifications, the Machine Learning improvements (that have happened over the last decade) were missed out.

Today, with Machine Learning algorithms, you can predict what product/service each of your app users will want next. With such razor sharp insights, you can target every user with extremely customized Push Notifications multiplying the probability of a sale. Such focused conversations with every user help you retain and grow loyal app users.

Executing millions of personalized conversations in real-time – now, that’s Mobile Marketing Automation in it’s true sense.

Now, how to choose a Mobile Marketing Platform?

Before choosing a mobile marketing platform, ask yourself the following questions:

  • Does this platform figure out whom to target, on its own or does it expect me to tell?
  • Does it suggest messages that meets your business goals- depending on what worked and what didn’t?
  • Does this platform care for my marketing dollars? Does it pick and show an optimum channel (Push, email, third party app /social display) for user engagement to make sure my marketing dollars are spent well?

It’s time to get machine- learning do the job for you!

Does this sound too complex? Take a look how Engage Commerce uses machine- learning to make your app marketing a walk in the park.

Experienced the power of machine learning already?

5 chances a fashion app missed to sell me a pair of shoes

Originally posted on DailySocial.

It was Friday night and I was at home watching the Wimbledon semifinal between Roger Federer and Milos Raonic. A huge Federer fan that I am, I usually try not to miss any of his matches, especially Wimbledon.

Federer has just broken the Raonic serve with that commanding single handed backhand of his. It was his turn to serve now and the camera, as they so often do, zoomed into Fed’s shoes to showcase the engraved letters RF and of course the Nike brand to the entire world glued to their television sets.

As I wondered how cool it must be to have your name engraved on your shoes, I also got reminded of the running shoes I needed to buy for myself. Of course no one’s going to engrave my initials on my shoes, I had to be content with the regular shoes at the retailer.

I opened the fashion app that I frequently bought from on my phone. But, it’s been a while since I bought anything online, let alone the app. The app had a new UI and looked cool. I browsed through few shoes of Nike, Adidas and Puma.

There were some nice ones and were up for great discounts too. I was in a dilemma whether I must buy a pair right away or do I go to a store the next day, try out a few pairs and then buy. Just then, I heard a massive cheer from the audience in the TV. Federer had held his serve to win the third set and take a 2 sets to 1 lead.

This is going to be good. I closed the app and turned my attention back to the TV.

Federer ended up losing the match in the deciding set and he even cried during the presentation. I was upset. I had forgotten about the shoe I wanted to buy. The weekend went by. I woke up Monday morning and realized that I hadn’t bought my shoes when I wanted to go out for a run. I should have bought it then, now I wouldn’t have time the whole week.

But hold on. I forgot, but how could the fashion app forget? I’m a marketing professional, so I got to a bit of thinking.

The fashion app must have tens of thousands of users logging into their app each day looking for various products. Not all of them are buying. At best, 2-3% of them would buy. What about the rest?

  • Why couldn’t the fashion app send me a push notification reminding me about the shoe that I wanted to buy? ‘Hey Dharshan here’s the shoe you almost bought!’ – simple isn’t it. This would have been the best thing. They could have sent me a push notification during the weekend and I would have made the purchase right there.{{cta(‘ada34175-cb59-49c2-92a4-e80198ba00c7’)}}
  • Why not an email? I have brought from the fashion app before and they send me several emails with promotions and offers. In fact I got an email from the fashion app on Sunday about their new home furnishing category of products. How did they miss out on the fact that I visited shoes on the app. An email with a reminder on the subject line would have definitely gotten my attention. I would have bought my shoes.

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  • And then there’s Facebook. I’m not the most active person on facebook but I did spend a few minutes over the weekend. There were other ads on my timeline but the fashion app didn’t bother showing me an ad of the shoe I wanted.
  • Of course there’s display ads on other websites I visit. An ad would have probably reminded me but I still had to take my phone and open the app and make the purchase.
  • There is the option of SMS too. Personally I don’t prefer getting spammed by brands with text messages. But I should admit, if I had gotten a text message with a link to ‘shoes’ page of the app I would have gone ahead and done it. But alas, I never got an SMS anyways.

I’m not an expert but I’m pretty sure people like feeling important. If I had received even one of the above mentioned communications from the fashion app, I would have felt valued and I would have certainly gone onto make that purchase. But now, I feel ignored.

If I find some time after work today, I will walk into a retail store and buy a sports shoe. There, fashion app, you just lost $50 revenue. Moreover, you just lost a customer. Who knows what would have been the life time value of me as a customer for you.

If you’re still wondering, I didn’t go on a run that morning.

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[Video] Airlines: Yield management with personalized offers

The biggest challenge faced by the airlines industry is ‘yield management’. In simpler words, the only question an airlines marketer is trying to find an answer for day in and day out is this – ‘how do I fill my seats on a week day?’

The difference between demand and supply is the starkest in the airlines industry. Traditionally, airlines have relied on blanket discounts for all users to encourage ticket bookings on their distress routes on week days. While this might help spike bookings to a certain extent, it simply cannot be a long term solution.

A sound yield management strategy relies on 3 key aspects:

  1. identify users with the right propensity to purchase
  2. create niche segments and personalize limited period discounts
  3. build a consistent user experience across all digital channels

Subra Krishnan, SVP Products at Vizury, explains in his article on Tnooz, these 3 steps through which airlines can close this demand-supply gap from a personalized marketing stand point.

Vizury’s Engage Travel is the growth marketing platform custom built for the airlines vertical. Here’s a quick peek at how Airlines can personalize offers at a user level and boost marketing RoI.

Watch video:

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With Engage, you can now

  • Integrate your yield management strategy with marketing for greater RoI

  • Personalize offers on a 1:1 basis, based on online behavior

  • Reach out to users with a consistent message across channels – Website, Push, Display, Social

The intuitive UI allows you to segment users and activate channels on the click of a few buttons.

Click Here to sign up for a demo or write to us at marketing@vizury.com and we will get in touch with you.