Showing posts with label Analytics. Show all posts
Showing posts with label Analytics. Show all posts

Wednesday, 27 July 2011

ThinkNear gets $1.6M to bring real-time analytics to local businesses

ThinkNear, a Los Angeles– and New York–based startup, caught my eye at the New York TechStars demo day with its data-driven approach to solving problems for local businesses. The company announced on Tuesday that it raised $1.6 million in seed financing from a gaggle of investors, including Google Ventures, IA Ventures, Qualcomm Ventures and angels David Tisch and David Cohen of TechStars, to help roll out their technology. That rollout got under way in New York on Tuesday. Other investors include Metamorphic Ventures, Real Ventures, ff Venture Capital, Zelkova Ventures and BoldStart VC.

The company’s approach is smart. It’s trying to tackle off-peak slow periods for local businesses, working to drive sales in those hours when foot traffic is light. That’s different from competitors like Groupon or others who often load up businesses at peak times, which can overwhelm them, limiting how much product they can move at one time.

ThinkNear is an automated system that lets businesses set their goals, input their historical slow times and how much they want to discount their products. Then ThinkNear pulls in a wealth of data from the store, and locally relevant information like weather, events and traffic to help figure out when a location needs more business. The system can push out location-based ads with discounts that are good for a limited time to help improve traffic during specific periods. Users then theoretically come in and present a code to redeem their discount, helping the merchant track the success of the program. ThinkNear also monitors the effectiveness of the ads to tune its future promotions.

Not only does ThinkNear have the potential to bolster traditionally slow periods, it’s also very simple to use for merchants. Many business owners are being asked to manage their online presence and work with sales teams to craft multiple discounts. They’re being called on constantly by sales people looking to tap their local ad budget. ThinkNear is more of a set-it and forget it solution, so merchants don’t have to manage it closely. It still has to produce results to be useful, but at least merchants are spared considerable logistical headaches.

Another of ThinkNear’s strengths is that it’s very data driven. Founder and CEO Eli Portnoy declines to go deep into the “secret sauce” of ThinkNear’s technology, but it’s leveraging real-time data analytics to really figure out the optimal times to run promotions. For example, an ice cream store may not need to push deals on a hot day, but if the temperature drops quickly or it rains, a timely discount can help propel sales. According to Portnoy:

Everyone understand mobile and local are happening and there is a convergence of the online and offline world, but everyone is focusing on taking the online world and stuffing it into the offline world. We’re taking an analytical, quantitative data-driven methodology from the web and taking it to local businesses. That’s our real mission in life.

ThinkNear CEO Eli Portnoy

Portnoy said the $1.6 million will go toward expanding the team of four employees and building out the launch in New York, where a number of businesses have already signed up. He said the next city is Los Angeles, where he believes he’ll be able to test the service on a metro area that represents the rest of the country better than San Francisco.

ThinkNear still has its work cut out for it trying to market its technology to businesses. That’s going to be hard for a small startup, when there are thousands of sales people calling on business owners. But if the start-up can get its foot in the door, I think businesses will see a lot of value in ThinkNear.

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Saturday, 25 June 2011

Four Key PPC Web Analytics Metrics You Should Consider

By Kirsty Lee


Watch your bounce rate

A high bounce rate is a good indication that your content isn't engaging.

PPC is an important strand of your web analysis. One of the cool things about PPC data is that you don’t need a lot of history to draw conclusions from it – a few weeks is enough time to give you an idea of how well a campaign is performing.


Google Adwords data is included in your Google Analytics data and includes metrics like click through rate (CTR) and cost per click (CPC). Google recently released AdWords API v201101, which allows you to more efficiently run reports, as well as implement campaign experiments and other recently released advertising features at scale.


But how do you track success after PPC visitors are on your site? What metrics should you investigate to ensure that you are getting high quality traffic and capitalizing on opportunities to convert?


For these types of performance metrics, you need web analytics! Here are four important metrics you should review on a daily basis to evaluate PPC campaign performance. 


1. Conversions


It pretty much goes without saying that conversions are the best metric to determine how a PPC campaign is performing. You should have your web analytics set up to record both online conversions (newsletter subscriptions, content downloads) and offline conversions (phone calls, offline campaigns).


To track online conversions, configure your web analytics to record a conversion every time someone arrives on a specific URL. In the case of web forms, this URL would be something like a thank you or confirmation page. For downloads, you might need to add a piece of tracking code that will register the download as a pageview.


To track offline conversions, see one way of doing this in our previous post on Measuring Success of Offline Campaigns in Google Analytics. There are plenty of other solutions out there for tracking other offline conversions (e.g. by telephone) which will integrate directly into your web analytics program so you only have to access one dashboard.


2. Bounce Rate


A bounce is when someone lands on a site and leaves without viewing any other pages. Your bounce rate will vary for each campaign. A high bounce rate may be an indication that your content is not relevant or engaging to visitors.


3. Pages Per Visit


The interesting data comes from a very low or a very high number of page views. Very low could mean that visitors are not finding content useful or interesting, and have resigned to go back to search results to find a more relevant page. A high number of page views could mean either you are producing interesting and engaging content (look at time spent on page for engagement), or that the visitor cannot find the content they are looking for.


In both cases, review the relevance of the page content to traffic-producing keywords, and make sure the information people appear to be seeking is on the landing page, or a click away.


4. Average Time on Site


It goes without saying that a higher time on site is better than a low one. Extremely low (0-1 second) — There is no way to read a page’s content in this amount of time. If there are a lot of visitors spending less than a second on the site, it may be the result of one of two things:



  • Invalid clicks – Check with your PPC platform to ensure you are not being charged for these.

  • Slow site load time – May cause people to get frustrated and hit the back button before ever arriving on the landing page. Low (less than 15 seconds) — Generally, those visitors who spent 10 seconds or less on a site quickly decided that they were in the wrong place. This may be because at a first glance they didn’t find any relevant information, see their keywords anywhere on the page, or were confused by the landing page’s layout.


Look at these 4 web analytics metrics and you will have a better idea of your PPC performance. Once you have gathered enough data to draw conclusions about which parts of your campaign work well and which don’t work so well, you can start implementing small changes and tracking the different outcomes. By taking this methodical approach you should be able to optimize your campaigns to get the best ROI.








Kirsty Lee works for We Are Cloud, a French company that created Bime, a SaaS Business Intelligence and Analytics tool. For more information, please visit http://bimeanalytics.com. .

This is a post from The Web Optimist – SEO in The Desert.


Four Key PPC Web Analytics Metrics You Should Consider is a post from: SEO in The Desert | More about Palm Springs SEO




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