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All Posts Tagged Tag: ‘BTW’

Home / Tag: BTW

Start-Up Watch COD:Offermatic users opt-in to receive targeted offers through their credit cards 0

The online targeting industry is built on the idea of “opt-out” – that users are participating until such time as they make an effort to opt out of data-based advanced targeting. Assuming a clear and prominent disclosure of practices and a genuine means of opting out,

I think that’s fine. I mean, something has to pay for 24/7/365 free access to the Library of Congress we call a computer that is sitting in our laps. Most targeting companies insist that if we moved to an opt-in model – in which consumers had to act to participate – then we’d have tremendous challenges driving revenue and profit that powers digital. I agree.

But a start-up called breaks with the herd, using a model in which consumers receive rebates, rewards, discounts, and other offers by linking their credit cards anonymously with the service. In other words, they OPT IN to connecting their purchase and browsing history in exchange for great values.

It works like this. You join – without, BTW, providing any PII beyond an email address, and then connect your credit card(s) to the service, giving consent to your bank to provide transaction information to the service. Based upon your purchase patterns, you receive offers geared to your interests, favorite stores, location, and so on. Discounts and offers are STEEP – 50% – 90% is the range for initial offers.

Offers are delivered in emails. The user clicks on an offer, visits the site, and loads it onto their credit card. Provided they take the desired action within the specified time frame, they receive the discount or whatever without having to clip or print coupons or send in mail rebates.

More than just transaction data are used for targeting. Offermatic also measures browsing history, searches, site visits, and other metrics to develop a more precise targeting model.

Here’s a video that serves up the concept for consumers:

So here’s a totally cool dimension for retailers – Offermatic can use the transaction data to serve offers ONLY to people with desired characteristics. So, let’s think back to that infamous Gap offer through Groupon. Remember the one? $25 for $50 voucher. 440,000 takers. Certainly drove store traffic. But how many of those people were already Gap customers. It stands to reason A LOT. After all, a 50% discount is even more likely to appeal to a current customer than a nonuser. So a lot of that 50% was basically profit thrown into a fireplace.

Groupon, mass. Offermatic, precise.

With Offermatic, Gap or Target or YOU could make the offer only to non-users, or lapsed users, so that the deal drives new business into your stores. OR, you could reward current users who make incremental purchases. The point is, the choice and precision are yours to control.

Post purchase, Offermatic can send reminders to drive additional actions, or reward users who publicize their purchases in social media. Plus, Offermatic can deliver reports that tell you who your users are, what impacts the program had on loyalty, and other great data that any marketing org would want. You also get benchmarking to show how your metrics compare to purchase patterns of competitors.

In my view, Groupon’s gonna have a tough fight on their hands when retailers get a close look at this outfit.

Thanks to ad:tech for publishing this first.

Posted on: 05-14-2011
Posted in: Oldest Living Digital Marketer

Start-Up Watch COD:Offermatic users opt-in to receive targeted offers through their credit cards 0

The online targeting industry is built on the idea of “opt-out” – that users are participating until such time as they make an effort to opt out of data-based advanced targeting. Assuming a clear and prominent disclosure of practices and a genuine means of opting out,

I think that’s fine. I mean, something has to pay for 24/7/365 free access to the Library of Congress we call a computer that is sitting in our laps. Most targeting companies insist that if we moved to an opt-in model – in which consumers had to act to participate – then we’d have tremendous challenges driving revenue and profit that powers digital. I agree.

But a start-up called breaks with the herd, using a model in which consumers receive rebates, rewards, discounts, and other offers by linking their credit cards anonymously with the service. In other words, they OPT IN to connecting their purchase and browsing history in exchange for great values.

It works like this. You join – without, BTW, providing any PII beyond an email address, and then connect your credit card(s) to the service, giving consent to your bank to provide transaction information to the service. Based upon your purchase patterns, you receive offers geared to your interests, favorite stores, location, and so on. Discounts and offers are STEEP – 50% – 90% is the range for initial offers.

Offers are delivered in emails. The user clicks on an offer, visits the site, and loads it onto their credit card. Provided they take the desired action within the specified time frame, they receive the discount or whatever without having to clip or print coupons or send in mail rebates.

More than just transaction data are used for targeting. Offermatic also measures browsing history, searches, site visits, and other metrics to develop a more precise targeting model.

Here’s a video that serves up the concept for consumers:

So here’s a totally cool dimension for retailers – Offermatic can use the transaction data to serve offers ONLY to people with desired characteristics. So, let’s think back to that infamous Gap offer through Groupon. Remember the one? $25 for $50 voucher. 440,000 takers. Certainly drove store traffic. But how many of those people were already Gap customers. It stands to reason A LOT. After all, a 50% discount is even more likely to appeal to a current customer than a nonuser. So a lot of that 50% was basically profit thrown into a fireplace.

Groupon, mass. Offermatic, precise.

With Offermatic, Gap or Target or YOU could make the offer only to non-users, or lapsed users, so that the deal drives new business into your stores. OR, you could reward current users who make incremental purchases. The point is, the choice and precision are yours to control.

Post purchase, Offermatic can send reminders to drive additional actions, or reward users who publicize their purchases in social media. Plus, Offermatic can deliver reports that tell you who your users are, what impacts the program had on loyalty, and other great data that any marketing org would want. You also get benchmarking to show how your metrics compare to purchase patterns of competitors.

In my view, Groupon’s gonna have a tough fight on their hands when retailers get a close look at this outfit.

Thanks to ad:tech for publishing this first.

Posted on: 05-14-2011
Posted in: Oldest Living Digital Marketer

COD: Mixtent aims at cracking the professional reputation nut 0

Thanks to for publishing this first

I first learned about in mid February, and was fascinated by both the notion of collective reputation measurement and the role it could play in making better hiring decisions. Let’s face it, making the decision to hire people is always a bit of a crap shoot. You can check references but rare is the person that cannot find three schmucks to vouch for them. Further, the fluid nature of job roles in the modern organization means that the same job title can require one set of skills in one company, and quite a different set in another.

We all know that hiring and retaining great staff are huge challenges on both the agency and brand sides. I am going to use the role of Media Supervisor as an example of why deep reputation information can be essential to making better choices. One assignment might require intimate knowledge of the bleeding edge, another an extraordinary mentoring ability, and the third the ability to build a stronger relationship with a client. We none of us are strong at everything.

What does is uses your personal Linked In network, and a binary either or rating system to provide a picture of an individual based upon the opinions of people that they are connected to.

You join Mixtent by connecting it to your LinkedIn profile. From there, the platform defines a range of skills connected to your experience, and has the community rate you versus other connections on those skills.

In turn, you get to rate people you know on their experience sets. As I mentioned earlier, the ratings system is binary. Would you rather work with person A or person B on a project requiring the given skill set?

The platform gathers all of the ratings of all of the people and gives you a percentile rank versus others with the same skill sets. Your percentile rank is only calculated AFTER you have received 20 ratings, which is designed to limit the impact of being flamed by an individual you are connected to. And to give the data genuine validity.

How will this be useful in hiring and management decisions? Well, for a start, it gives you a more quantitatively valid view of an individual’s strengths. It’ll help you decide whether candidate A or candidate B might be more appropriate for that Media Supe assignment that requires strong managerial skills. Because you won’t be relying on a few interviews and self-selected references.

BTW, your ratings of individuals are kept private – that’s another inherent strength of the system requiring more than 20 votes before it calculates your percentile rank. That way you can be honest without fear of repercussions.

This is a new service, and for now only your connections can see your rankings. Additionally, if you see your ratings and dislike the answers, you can opt right out. Tech Crunch said that this is important to building a successful professional reputation platform. In their words:

Your peers can vote on you anonymously, so you don’t have the LinkedIn issue where people glad-hand recommendations for one another, but there is no way to enter text so the site doesn’t evolve in the defamation morass of Honestly either. Also, unlike Honestly (born as Unvarnished), you have to opt-in to Mixtent, and if you don’t like the results, you can opt out. I think that’s essential to any reputation system. If you build a good enough product, people will use it without being bullied or forced into it.

I can only guess where Mixtent is going. But I think the model is well designed, and the information very valuable. It’ll become even more valuable as the ranking algorithms get more and more accurate. Keep an eye out for this team – I think they are on to something very valuable.

Posted on: 03-21-2011
Posted in: Oldest Living Digital Marketer

COD: Wishpond – Putting virtual in service of local bricks and mortar 0

The percentage of retail driven through ecommerce continues to grow, but it’s still in single digits. That being said, there is no doubt that consumers are using the web to do research on products, especially for more considered purchases.

Wishpondis out to drive more sales to brick and mortar, using geolocation to help small and large retailers make consumers aware of what they have in stock and ready to take home today.

Imagine you are looking for a fairly high end Nikon. You’ve done your research online, but now you are ready to buy. You COULD make a purchase through Amazon or Fry’s online, or you could fire up Wishpond and see if it is available anywhere nearby. Wishpond lets you search local retailers’ inventory to see who might have the item and for how much. Let’s say three retailers report having the item. You can then consider the trade offs of price, reputation, and distance to see if one of these retailers might be a better place to buy than an online store.

There are benefits for all of the players in the retailing ecosystem:

•For consumers, Wishpond gives an easy way to compare prices and the opportunity to get the good today. They can also “make a wish” meaning that they can offer to buy something at a certain price and see if any local retailer bites.
•For retailers, it provides the opportunity to spend ad dollars on people actually looking to buy, and a chance to level the playing field by communicating local availability of an item.
•For brands, the opportunity to communicate participating retailers gives another means of supporting your brick and mortar distribution system, and a way of growing sales. They could also advertise on the platform to impact buying decisions
•For publishers, the platform provides the opportunity to grow relevance to readers by making things like product recommendations more actionable. Not only can you recommend an item, you can now show consumers exactly where they might want to buy it. As such, it might also be a good advertiser lead gen tool.

This is an ads-supported platform. Retailers can join for free, or they can join and take advantage of the opportunity to do hyper local and highly targeted advertising to very likely buyers. They can even package up sales leads of people looking for an item.

We all know that the big retail winners over the past couple decades have been big box stores. But this platform levels the field, enabling even small retailers to capitalize on the technology and sales opportunities it surfaces. Though of course big box stores are also welcome to participate. And no doubt are and will.

One of the things that makes this a compelling platform is that Wishpond can plug into existing inventory management programs so the retailer doesn’t need to manually input items and manage inventory levels. Instead, it’s inventory speaks for itself.

There are other resources in this space, not least Milo and Google Blue Dot. But one of the ways that Wishpond stands out is that a business or pub can participate easily using an embeddable widget. These widgets can search inventory, show local locations, and even be embedded into distributed presences in social media. They also have an open API, which is helping them differentiate by shaping themselves as a platform rather than a retail search destination.

BTW, their blog is also an excellent resource if you just want to learn more about local and shopping and retailing in today’s environment.

Posted on: 03-21-2011
Posted in: Oldest Living Digital Marketer

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