Top 5 Alternatives to Google Analytics, for Ecommerce

Say you’re running an online store. Chances are you are using or plan on using Google Analytics. It’s free, it’s popular and there are tons of info out there to help you get started and optimize your sales stream.

But there are downsides too. First one – Google already knows a lot about you and your customers. You might want to keep some things discreet, right?

Second – Google Analytics is an one-size-fits-all type of product. Sure, it has plenty of features but chances are you’re likely to get lost in some of those features. Even if you don’t get lost, you’re likely to spend a lot of time digging through somewhat useless data, while at the same time, missing out on very important bits of information.

Third – real time reporting is pretty limited, if you’re running the free version. Once you get over 10 million views you’ll have to switch to the paid version, costing you north of $150 000. But then you can also try some more advanced reporting tools.

Of course, there are plenty of traffic analytics tools out there. Some have really great interfaces and features. But as an online shop owner or manager, you have to look at what works best for your store. Have a look below:

1. Mixpanel

Mixpanel Funels
Mixpanel Funnels

Mixpanel is great choice for small and mid-sized business that sell. Whether we’re talking about an online retailer, a hotel selling reservations or an iPhone game developer selling game upgrades – it is a great tool.

Even the way Mixpanel tracks actions and charges users is a great fit for online retailers. Ecommerce sites don’t really need too much intel on page views. What really matter are actions – the number of times sometimes has clicked the “buy” button, the number of times users download a brochure or the number of Google Ad visitors that turn into customers.

Mixpanel calls these actions data points, and this is a great news for startups and mid-sized businesses.

It’s tailored around five basic functions:

  1. Segmentation – allows for better understanding of user behavior and splits user groups according to actions.
  2. Funnels – you might be familiar with funnels from GA. But once you get to know Mixpanel’s take on the funnels, it seems that something has dramatically changed. Funnels can be added on the fly and viewed retroactively, easily.
  3. Retention – it’s not just how much you sell, but also – who keeps coming back.
  4. People – unlike GA’s confusing take on users, Mixpanel builds profiles ecommerce store owners can understand. The system collects data that can be browsed individually or segmented. One great feature is the notifications option, where you can mail, send SMS or push notifications to users, based on automated or manually segmented profiles.
  5. Notifications – mentioned above, it is a great tool that improves the analytics platform, allowing you to also communicate directly to consumers.

Pricing

Pricing is free for less than 25 000 data points and it can go up to $2000 / month, for companies with more than 20 million data points.

 

2. GoSquared

The redesigned GoSquared app
The redesigned GoSquared app

GoSquared is a great piece of engineering and with its redesigned interface – easy to use. It serves over 40k businesses and it has a special area developed strictly for ecommerce owners.

When it comes to ecommerce, GoSquared packs a lot of power in a simple interface. Just like most other applications on this list, it puts a strong emphasis on the targeting users as potential customers and tracking their actions and behavior.

The Metrics work toward providing clear insights on how revenue is doing. The analytics tool provides info on social media influence on sales and data on best performing products.

One really useful set of tools is what GoSquared calls Predictive Analytics. Previously discussed on Netonomy.NET, predictive analytics can mix past and present data to determine possible outcomes in the future. It can be used to predict traffic, sales or best selling products, to name a few.

GoSquared also mentions their ability to send Differentiated Reports, based on specific team member’s needs. One for the CEO, one for the marketing team, one for the … well, you get the idea.

But if there is something that really sets GoSquared apart – this is the Developer API. Using this, developers can build truly dynamic online stores, that respond to customer behavior and profile. From info on previous purchases, location, language and others, online stores can be set to respond to specific customer needs.

Pricing

Pricing can be configured here and starts at $32 / mo for 100k pageviews and 100 transactions. It can go north of $640 / mo for more than 10 million pageviews and more than 10k transactions. You can test the application in a 14 days trial.

 

3. FoxMetrics

analytics-foxmetrics

Foxmetrics has some nifty features when it comes to ecommerce and online retail related options. It is light and easy to set up, it works on both web and the mobile and it is focused on helping you increase conversions.

Although Foxmetrics is not 100% focused on ecommerce related (they also provide support for online publishers), it does have some great features you can use:

  1. People – using this section you can understand customers and their actions and can sync this data into company CRM software;
  2. Ecommerce – Foxmetrics provides support for useful KPI’s and advanced reporting dashboards. Using customer data, it can build  product relationships, shopping cart reports and can respond with automated actions;
  3. Subscription is an useful tool for companies working with periodic purchases. The product can report user data, conversion and churn rate, as well as detailed info on separate plans;
  4. The Marketing and Triggers options allow for personalized marketing and response, based on referral and user actions.

Pricing

Although Foxmetrics does not provide a free option, it does provide a 14 day trial to test the features. Plans range from $50 to $120 per month and beyond, for enterprise users. However, as an ecommerce user, you’ll be stuck with the $120 plan.

 

4. Woopra

analytics-woopra

Woopra  is a great way to understand your customer and their history browsing your store. You’ll be able to get behavioral insights from customers, run advanced or preset analytics reports.

By tapping into Woopra’s Funnel reporting section you can discover bottlenecks in the conversion path.

The product also promises a good segmentation on best performing customer groups and even build segments based on funnels.

Pricing

The pricing starts with a free version that allows 30 000 actions (similar to Mixpanel’s data points). The small business plans range between $79.95 and $1199.95/mo.

 

5. KISSMetrics

analytics-kissmetrics

KISSmetrics follows a simple assumption: you must get to know your users … ahem … customers. That and the fact you should pay attention to their brand name.

The promise KISSmetrics makes is that all your data will be connected to real people, with real actions. Once setup, you can see where people are, what and why they buy your products and in some unfortunate cases, why they don’t.

Features include funnels, cohorts (groups with similar interests), revenue in real time and the metrics you’re familiar from GA. The things that really set the product apart is the data export feature for further analysis and its A/B testing options, both a great fit for customer profiling.

Pricing

Pricing for the KISSmetrics product starts at $150/mo for up to 500 000 events and goes up to $500/mo, when your webstore reaches more than 1 million events. Once you pass the upper threshold, just like all others, you get to negotiate your pricing.

 

Predictive Analytics and Why Companies Are Stalking Their Customers

Tomorrow is all about Big Data and how best can you handle it. See, companies don’t need more data. Most medium to large companies either have the data or ways to get it easily available. The problem is – most of them don’t know how to handle it.

Here comes the boom: Predictive Analytics is *the thing* nowadays. Long gone are the days when merely registering data, processing it and acting upon the findings in the next fiscal year was enough. Right now the fastest growing companies register data, analyze it and respond to it in real time.

Predictive analytics and predictive personalization – how do they work?

Hunch Recommendation
Hunch, now part of ebay, offers personalized recommendations based on personal infromation

We all leave trails behind. Our shopping habits, our marital status, our social groups, the shows we watch and gadgets we buy – all these and much more are trails and they are in some database, somewhere. Using this data, or whatever is available at any given moment, predictive analytics software can determine our future actions through two types of programmed responses (it’s a little bit more complicated than that, but you’ll get the picture):

1. Rules Based Personalization – “If this than that”. Basic personalization. Ex.: Customers click on an ad, enter our website and we can determine they are from New York. Let’s show them our stores in New York first. They click on our product catalog, select the high-priced products. Bang! We now know they have a medium to high income. This kind of responsive personalization does not really make use of any kind of predictive analytics. It just reacts to actions. It does not try to predict them. This is a job for…

2. Predictive Personalization – this is something we, humans, can do easily. Machines, not so much. Let’s say our sports store has a sales person with a decent IQ who’s at least a little bit interested in the customers checking out the merchandise. He notices customer X has tried on at least a dozen of sports shoes in the last hour. He walks to the customer and asks him “Hey, can I interest you in this brand new snowmobile? It’s 10% off. Oh, wait that is stupid. That just what old-time ads would do. He would actually ask the customer if he can help him find some shoes that fit and look good. That’s basically what Predictive Personalization is all about: 1. Analyzing the data real time / 2. Using context to pinpoint the best potential recommendation and 3. Personalize the output.

In case you were wondering – yes, there’s a little bit more science to it but the previous example shows what the buzzword stands for. If you are interested in the subject or you’re a future Predictive Analytics Expert you can have a look at “Personalized Recommendation on Dynamic Content Using Predictive Bilinear Models”, on how Wei Chu and Seung-Taek Park of Yahoo Labs used Predictive analytics to recommend better content on Yahoo’s front page.

Why companies use Predictive Analytics to stalk their customers?

You know why Facebook stalking is so easy? Because people want other people to know about their interests. The Millennials, the digital natives, generation Y – they are today’s youth and they are born and living online. They offer their info, they share their interests, they make their photos public. No more mass message. Each and everyone expects to be treated as an individual.

Companies that do not “stalk” their customers are going to be left behind: Amazon is personal, Facebook is personal, Google is personal. Most of the top online retailers are personal and they make customers’ shopping experience unique.

How about offline? Yes, 5 years ago we couldn’t have had any kind of Predictive Analytics or Personalization offline but the iPhone changed that. Now smartphones fill the gap between the data stored online and offline activities. Companies are now tracking consumer behavior through mobile activity and make use of predictive analytics to address individuals needs and wants … well .. individually.

Acting on data is not enough anymore. It’s acting on data NOW that’s important.