Use the data you already have. Most companies already have access to customer interest (implicit or explicit), engagement and transactional data that they can leverage to understand and anticipate customer needs. The challenge is capturing this data to create the visibility and analytical insights that marketers can act on to identify and respond to customer needs.
Which brand are you more likely to continue to do business with: the one that recognizes your recent dining room chandelier purchase and provides helpful communications about possible accessories, like a dimmer switch and light bulb options? Or the company that sends you a promotional offer for a dining room chandelier just like the one you bought, because they recognized your browser history but didn’t capture your last purchase? OK, so the answer is obvious. However, this demonstrates why marketers need to leverage the engagement and transactional information they already have to enhance the customer experience.
Bottom line: Use the data you have to put your customers in context. It will enable you to better anticipate their needs and give them what they want, when they want it.
Contextualize consumer interactions and preferences through analytics. Do you know how your customers engage with and buy from you? You may find that customers browse and gather information on one channel (in-store, online or via catalog), purchase on another channel (online or call center) and ultimately receive their merchandise in yet a different channel (local retail store pick-up). This type of cross-channel consumer behavior demonstrates a preference for using whichever method gives the most convenience, ease of use and speed of service delivery. When marketers analyzes their customer interaction and preference data, they can:
Take the example of customers who don’t care about free shipping or percentage-off discounts, but always respond to BOGO offers they receive online that they can redeem at their local store. By analyzing the types of products customers purchase based on the offers they receive and the channels they engage with and buy on, marketers can understand and deliver experiences that meet the contextual preference expressed by a customer’s behavior.
Automate the insight-to-action cycle. Companies that use analytics to enable responsiveness are able to shift from a reaction mode to a proactive, anticipatory mode of engagement. This shift requires marketers to step into the shoes of the consumer. They must understand the customer journey and be able to identify the questions and needs that consumers will have along their path to purchase. The next step is to anticipate the engagements that are most likely to answer those questions, reduce uncertainty and increase convenience and ease of use for the consumer. Once the customer journey and anticipated questions and needs have been identified, communications can be automated and triggered by specific customer behavior and/or stage in their journey to create a continual insight-to-action cycle.
Think about the car rental company that can prioritize offers and information provided before, during and after a trip by considering data it has about the customer (such as attributes collected through its loyalty program and responses to past offers). For example, the preference and behavior data of a customer might include the type of car customers typically rent, their rental frequency, whether they travel for business or pleasure, the locations they usually rent and pick up from and if they usually select economy or full size. All of this data can be leveraged by the car rental company to provide contextual information to support additional value-add services, such as pre-trip planning (local hotel, restaurant and entertainment offers) and post-trip information (customer loyalty status and appreciation offers).
The most successful marketing organizations are the ones that can access information on demand with an analytics-driven approach to understanding their customers’ context, anticipating the next best interaction and executing it through the preferred engagement channel. This approach is what we call present tense marketing. Organizations operating as present tense marketers have the capability to continually capture and assess the dynamic consumer state and respond automatically in real time, providing a customer experience that truly wows.
Good article, but let's look at two of those examples. With the chandelier, the best time to offer accessories such as light bulbs is on your website, as soon as a customer puts the chandelier in their shopping cart. Few people wait until they receive a reminder email before thinking about buying bulbs for their light. And re "customers who don’t care about free shipping or percentage-off discounts, but always respond to BOGO offers", you are very unlikely to have enough purchase data to recognize most customers in this very specific category. So by all means use the data you have, but try the simple things. For example offer popular items first and use abandonment emails to increase the contact rate for active shoppers.
Pete...I have to agree with you but at the same time if you are collecting data in real time and combining it possibly with historical purchasing data, if provided by the client, it is possible to further customize the shopping experienc in "real time" as we do here at Certona.com When it comes to email, whether its marketing, transactional and/or retargeting, the ability to also personalize each message with any type of asset, whether it be products, videos, banners, deals, etc is possible again and stacks the odds that they will click back into the site. The key is to personalize, based on each unique customer and not just collaborative/wisdom of the crowd filtering.
Pete, thanks for your comment. I agree with your thoughts on trying simple things during their shopping session and or within an abandon program. However the idea here, is really around the idea of starting to capture and use both deep and wide data to determine the types of offers people respond to based on previous purchase behavior to individualize the messages and experience.
Mitch, thanks for your comment. You are correct, the whole goal is to start to mine deeper data sets to further personalize individual expereinces beyond specific segmentation strategies and or lifecycle programs.
Thanks Katrina...you are "spot on" but taking it to the next level..we are the only technology that can deliver recs in "real time"...no cacheing and delivering later...has to be "real time" for a true personalized experience. If you are not partnered with a technology that can do this, then you are correct...next best is to mine deeper data sets to personalize but more on a "wisdom of the crowd" mentality.
You are spot on Mitch. The mining/analytical insights have to be determined and delivered in "real-time" to create that individual customer experience. Thanks!
Nice article Katrina.. you bring up a very sage topic and without a framework to think/act/optimize the concept gets trampled on. Certona "IS" cool and in use in more places than I can even contemplate and most retailers I've met with have used, tested or still use it today. , yet Pete as usual is giving a practioner's view that is very wise... Many don't have access to the data real-time to setup programs like this, many can't operationalize this and many don't connect real-time with email as the effort outweighs the value... I find that few marketers are really leveraging purchase data with behavioral data anywhere near realtime... that would affect "email programs"... Good bit, good discussion and there are no wrong answers here, only contextual opinions and I love posts that get the conversation going... knowing the one size need not fit all... Cheers!