Are You Ready for Smarter Spenders Bursting Your Bubble?
Is your company, web site, or business model ready for the smarter customer spending habits being created by data transparency? The world of data transparency is one where anyone can access, slice, dice, pivot, and extrapolate on their own about your products is almost here. The cost of doing so, like other commodity driven resources is quickly approaching zero. If your business doesn't embrace it then you are going to be one of the people complaining about the "bubble bursting" on Web 2.0.
What's happening right now is that businesses and customers are on the precipice of learning how to thin slice through what's been labeled "information overload". Here are eight things you need to know in order to thrive in the age of information transparency and smarter customers.
- Your customers are only going to get more access to data every day and never less.
- Data is going to become increasingly consumable to people that don't know anything about how to create pivot tables in excel.
- Every new bit of data will encourage humans, who naturally seek connections and meaning, to to ask ten times the questions they may have previously.
- The data is going to be used poorly while people learn to correctly thin slice. You might not like the stories customers tell on their own to answer the aforementioned questions.
- You will be as unable to control access to the data, metrics, and subsequent analysis as you are able to control your singular corporate messages an PR today.
- Because information is so cheap to distribute through the series of tubes it will only take one person to discover and aggregate this kind of information. Really only one customer needs to be smarter and the rest will just listen to the "smart ones", but you knew this already.
- The flow of information goes can go two ways. This presents an opportunity to learn as much or more about your customers than they know about you.
- Thin slicing the data will open more doors to micro-message and micro-target your features, services, or brand to customers.
Here are some examples and trends that demonstrate the approaching freefall in the cost of public data mining.
- Search engines will make collecting hard data simpler. Most of them already returns hard numbers instead of guesses in the form of links. Today you can search for APPL and get a stock price back instead of a link to a page that references the stock. You can search for ichiro and see his career statistics. How long before "Baconader calories" returns the nutritional information directly or "Xbox Failure Rate" returns the total unique number of "red ring" incidents and the failure rate?
- Technologies like wiki's make collaborative document editing simple. Google Spreadsheets has taken the first strides toward collaborating numerical analysis. What happens when someone opens wikipedia for data mining?
- Currently sites are now popping up that encourage this sort of data collaboration. Check out http://www.voterwatch.org/ & http://www.revenuewatch.org/ for collaborative pollitical dirt digging, http://www.plebble.com/analysis.php for public data analysis, or http://www.kidsdata.org/ for examples of public health records data aggregation. The next logical step is for these aggregation technologies to improve over time and enable the users themselves to submit and refine the data.
- Communities are already starting to do their own data mining to enable self policing. Wikiscanner is a good example of this. How long before they are policing your products, communities, and marketing efforts.
The first question to start asking yourself is what will happen to your business when your clients and customers can go beyond user reviews and can become immediately familiar with your failure rates, cost of goods, how popular your site is, percentage of other customers who repurchase, and how many people actually click through the average ad on your web site? It's common sense to be looking at these numbers anyway, but the twist is now realizing that this sort of information either is or soon will be public knowledge.
The next set of questions you should be asking is how can you take advantage of the data transparency. Here are some untested suggestions to think about. 🙂
- Your own data mining needs to be taken to the next level. You need to go beyond answering the basic questions and start performing trend analyses and attain the ability to predict what bits of information (good and bad) your customers will discover next. If you don't already have, for example, a tool/process that lets you find out what people are doing and saying in your customer communities then you need one. It may not seem that way, but there is still a delay between the first person that says "I have a red ring", the next fifty, and it becoming front page news. The data can just about predict what's going to go from 1 to fifty to millions.
- A risk/reward analysis could be performed on the data that will be uncovered. What will happen if the exact failure rate is known or if people know how willing your site visitors are to convert into paying customers? On the other hand; Is this data something that you should be sharing more broadly because you know it's better than the competition?
- What data and models can you be transparent about? It's may no longer be acceptable to throw out a great customer satisfaction number without showing the numbers used behind the figure.
- You should consider enabling your own public data aggregation initiatives. Look at how Ideastorm took loud, but separated voices, and gave them lightening rods focus their energy. Because they are hosting these conversations the cost of data aggregation about customers suggestions went from wildly expensive public surveys and "buzz metric" analysis to near zero in comparison.
What do you think? Are your customers and clients getting smarter with cheaper data? Do you see an "adjustment" in spending in the "Web 2.0" space coming?
Have I mentioned we're working on a Reporting Server?