Do you think your group is forward thinking and tech savvy?
How about your customers? They are probably smarter than you think..
Can you describe cloud computing? What about when you were 10?
Our friends over at Accenture put this together.
There are few things that seperate the good marketers from the bad. In our opinion contact strategy is one of those things that few organizations understand and all should consider. When you are trying to decide who you should contact, through what channels and how many times, here are a couple of things to think about.
1. Not all customers are created equal - Nor do they have the same appetite for your marketing efforts. We recommend you spend time looking at your customers and how many times you contacted them in the past. A good cluster analysis will begin to help you understand that some groups prefer 10 'sale' messages and 2 'partner' messages before opting out. Put this cluster with other customer breakouts and you have the basis for your contact strategy.
2. Not all messages are created equal - As we eluded to above, you can not simply look at the recency and frequency of your messages to determine how much is too much. You need to understand the message types or objectives. Customers have varying appetites for your credit card solicitations and that appetite is much different from your best customer sales messages.
3. Implementing your strategy may be harder than developing it - So now you know what you want to implement. Customer segment X gets Y transactional messages a month and Z surveys a month. But how do you insure that they only get what you've prescribed? There are a variety of ways to accomplish this with either process changes and / or technology solutions (One of our favorites is Unica's Optimize.).
If you are considering a contact strategy for your organization, we would love to help you understand your customers and improve your communications.
As more is written about various categories of marketing, we can't help but think analytically about the implications of approaching marketing problems given their categorical differences. Of late, much has been written about 3 specific communication or marketing types:
- Paid media
- Owned media
- Earned media
This breakout is logical, however any marketing breakout must be based on some common public thinking about 'channels'. Thus customers must interact and respond differently to those categories. During some of our most recent analysis, we found that applying some of our traditional segmentation matrices to the response indicators for these categories told a specific story for one client. Various customer types respond distinctively different and to varying degrees to each type of marketing.
Now this might not be ground breaking on it's appearance, but if an organization could understand it's customer base to the point of actioning it's marketing toward the most profitable segments within each category, therefore maximizing it's return in paid, owned, and earned, great efficiencies could be made. It would be apparent which channels need the most focus and are the most profitable for an organization.
In the case of owned or earned media, organizations could save large portions of marketing dollars from being wasted in the paid category by maximizing 'word of mouth'.
Yet I digress. All this to say, understanding one's customers and the preferred and most profitable interactions of those customers is what creates efficient and effective marketing. Paid, owned and earned is no Earth shattering new marketing breakout, but if this is how marketing thinks about it's channels, it is how analytics should organize to help them understand where their attention should be focused.
If you have worked with marketing technologies for any length of time, you've encountered this problem. How can we integrate our CRM with the rest of our organization? How does CRM interact with our call center, website, applications, database, loyalty system, etc., etc.
We've been there.
Throughout our travels, we've picked up a few tips. Hopefully they'll help you.
- Tight integration is dangerous. Just don't do it. - Marketing technology changes faster than fashion. Today's latest and greatest is quickly replaced with tomorrow's new market maker.
- Integrate through marketing concepts not technical application specs. - Abstracting technologies through the use marketing concepts like 'campaign', 'offer', 'contact history', 'registration', 'enrollment', etc. Define what these mean for the organization and build a data structure flexible enough for all applications to contribute to those concepts.
- Databases and services are the lifeline. - Long term success hinges on ease of use and flexibility. Simple services allow for plug and play scenarios. Well designed databases create environments that record interrelated transactions based on their role or concept. This makes business people happy. They can measure, analyze and predict without spending precious hours compiling, cleaning, and organizing data.
- Think replaceable. - Always remember that what you are adding to your technology stack could be replaced in a year and you will need to re-integrate something else. How much of your current work will be thrown away? Minimize the one-time development and maximize your efficiency and cost savings to the organization over the long haul.
We like to think we aren't integrating technology. We are simply making all of our applications play nicely together.
There is much more to this topic, but these 4 tips can minimize your stress for ears to come.
As any good analyst knows, working with data is not the problem. Good analysts have the skill necessary to combine, split, merge, slice, aggregate, or summarize data any way you can imagine. However, is that enough?
What good does data do if you can't communicate its meaning in a logical way. The day of sending a spreadsheet with pivot tables are heading out the door. Today users are wanting more. They are expecting more. And why is that?
Here are a few reasons users expect more from their data experiences:
- Google Analytics
These are just some of the companies leading the way in user interface. The days of cheezy HTML or excel graphs won't cut it. Users quickly see they have to work to understand the information and move on.
A complete toolbox of data tools and a team of professionals with tool experience. Today's environment requires (along with some of our favorite vendors/partners):
- a storage solution
- an analysis tool
- a display layer
If your organization isn't firing on all analytic cylinders, let us know. We have the tools, relationships, and people to move you to the next level. We have a proven track record of moving the needle through the integration of data into decision making.
What programs do you belong to?
If we asked you to list all of the loyalty programs you belong to, you could probably rattle off half a dozen or so. Then you might stop and list off 10 more that you joined but don't use. In reality, the exercise would be less time consuming if I asked you to list retail outlets that don't have a rewards program.
Why does everyone want you to join their loyalty program?
How do you use the data to improve sales?
As an organization that thrives on measurement and strategy, incentive programs are a gold mine. Droves of transactional data that can be worked to produce insightful nuggets of information regarding a specific group of customers that can then be leveraged to conduct relevant marketing.
Specifically, we help with questions like:
- What kinds of offers are most effective with this group of customers?
- What customers are the most valuable?
- What types of creative / messaging receives the highest response rate?
- Given my budget, which marketing efforts or mix thereof provide the best return?
- What cross-sell products are most successful with this customer segment?
- What communication schedule (frequency) is appropriate?
- etc etc..
At what point does it makes sense to engage analytics in loyalty programs?
The earlier you consult with analytics during your program / campaign design, the more successful you will be. We help clients with their customer segmentation, targeting, customer experience, and response/investment measurement and reporting.
Ultimately, we are here to improve your marketing. If you are thinking of beginning a loyalty program or would like to improve the return on the one you have, please contact us for a custom assessment.
In recent weeks, we have began to work with a new company, Data-Applied Inc. You may have heard about the release of their new software for business intelligence and data mining. The application is a new breed of analytic tool.
For years, AFHood Analytics Group has been building custom Flash / Flex solutions to meet organizations needs. However, Data-Applied is a new leader creating software that allows users to intuitively visualize, extract, analyze, and mine data.Their new silverlight based suite not only looks impressive, but has the power to tackle difficult data scenarios.
We don't normally share posts from other blogs, however this article resonated well with us.
Andy Hasselwander wrote a post regarding the word segmentation. It has to be one of the most over used buzz words in business today. We consider this one of those words users throw around when they are overwhelmed with customer data.
Andy does a good job outlining the process businesses should go through to define the type of segmentation they need. Additionally, he states the problems with trying to segment customers by every element (value, product, creative, promotion, channel, targeting) is impossible in one uber-model. However, who says you can only have one segmentation model?
Often we find that sophisticated customers need more than one model. The process for defining the model is the same. Yet different groups require a unique view of the customer base.
Kudos to Andy for a well written post and thoughtful view on segmentation.