Predictive Analytics are all about finding the insights that will 
help you understand what might happen in the future. They help you 
recognize patterns in historical data, repeated transactions, and 
relationship cues. If you use predictive analytics effectively, you can 
facilitate a more proactive business approach.
There is a gigantic and horrifying sea of predictive analytic 
research & theory out there – so much so that it could make your 
head spin. So, for the sake of sanity, let’s hone-in on three of the 
major predictive analytics types and how they can make you a smarter, 
savvier, sales or marketing professional.
The three predictive analytics we’re going to discuss are:
- Sequencing
 - Cross-Selling
 - Lack of Action
 
1. Sequencing
Simply put, sequencing has to do with analyzing probability. If a 
target performs action A (downloads a whitepaper), followed by action B 
(clicks on a pricing page), what is the probability they’ll perform 
action C (buy the product)? This concept stems from the work of a 
Russian mathematician named Markov. Markov researched probability theory
 and determined that action C is equally as likely to occur if actions A
 and B occur first.
Seems easy enough: all you do is look at the historical patterns of behavior for A and B to determine your C outcome.
But, what if you don’t have a lot of historical data?
If you don’t have enough historical data to analyze how two or more 
events affect the desired outcome, there’s another way. Part of Markov’s
 model includes an assumption about the data. Not surprisingly, it’s 
called the Markov Assumption. If you consider only the last successful 
event to predict future behavior, you can assume the probability between
 that single event and the desired outcome is about the same as it would
 be otherwise. For example, ideally, we’d like to see Jane download a 
whitepaper, click a pricing page, and then buy a product. But Markov’s 
Assumption says if someone who visited the site before Jane downloaded 
the whitepaper and then bought the product, it’s likely that Jane will 
do the same. She doesn’t have to download the whitepaper AND click the 
pricing page for us to assume she will buy the product.
What does that tell us? We don’t need gobs and gobs of historical 
data to start a decent sequencing pattern. We can begin to discover 
sequences based on one action that leads to a purchase. That means you can initiate data sequencing today based on your most recent successful conversion, and then continue to tweak as you gather more and more historical data to cross-reference.
So what are some ways we can use sequencing analytics for better sales and marketing?
Marketing:
 One way marketing can use sequencing is with behavior-triggered email 
campaigns. If a person takes actions one or two, they are put into a 
specific track of the campaign. As you monitor the actions taken 
throughout each campaign, you’ll begin to recognize the patterns to 
customize your messages going forward.  Two tips to keep in mind for 
your behavior-triggered campaign:
- Knowledge first, branding later. Create a campaign 
filled with rich, engaging content that will help the recipient. As they
 move through the cycle, sprinkle in your branding. The point is to 
establish trust and position your company as an insightful resource. 
Once the trust is earned, everything else will follow.
 - Use mobile to help you sequence. More people than 
ever are reading emails on their mobile devices. Optimize your campaign 
for both desktop and mobile to help get a better grasp on your audience.
 Are you seeing more conversions from mobile? Weave that into your 
sequencing analysis to refine the approach. For example, make it easier 
for them to take action via mobile by replacing hyperlinks with buttons.
 Buttons are bigger and easier to touch on smaller screens.
 
Sales:
 Sequencing fosters proactive approaches to the buying cycle. For 
example, if someone visits your website, downloads a whitepaper, and 
requests a free trial of your product, you can assume they’re pretty 
interested. Using the sequencing patterns, you can then predict that the
 next time someone downloads that whitepaper, it’s probable that they’re
 interested in the same thing. So, the proactive approach would be to 
reach out to that prospect. By reaching out you open dialogue that may 
be able to speak to any hesitations or concerns they have. IMPORTANT 
NOTE: There’s a right way and a wrong way to reach out.
Wrong way – “I noticed you downloaded our whitepaper on CRM integration this afternoon. Let’s talk about it.”
Right Way – “Hi, I’m reaching out to local IT professionals about CRM integration. Is that something you’re pursuing at this time?”
Don’t act like a stalker (even if your sales process inadvertently 
makes you one). The right approach can make the sale without seeming 
creepy or overwhelming to the prospect.
2. Cross-Selling
What do you see when you make a purchase on a website like Amazon? As you go to check out, it shows you suggestions such as: People who bought this TV also bought this HD cable and these DVDs. They’re
 using analytic data to figure out which companion products you’re most 
likely to need/want based on your purchase — it’s cross-selling. You can
 use predictive analytics in the same way.
Just as people who buy a TV often end up needing cables, people who 
buy one of your products or services may end up needing a companion 
product. Look back through transactional data from the last two years to
 see which products were most often purchased together. Then, use your 
predictive analytics strategy to plan the cross-sell strategy.
Pro Tip:  Focus on your current customers first when implementing a cross-sell  strategy. First of all, you have more data available to you about their  buying habits. Second, research has shown that cross-sells to existing customers are 60-70% more likely to be successful than those aimed at new customers.
Your CRM system contains much of your key customer data – so use it! 
If your social media feeds are integrated into your CRM data, that’s 
even better! Use pattern analysis of Tweets, Shares, Likes, etc. for 
deeper insights. Multichannel analysis!
You can start implementing your cross-selling data by:
- Showcasing companion products together on your website
 - Creating a bundled offer for two of your most popular products or services
 - Automating cross-selling in a confirmation email (Think Amazon’s “Frequently bought together” tactic)
 
3. Lack of Action
The first two predictive analytics we covered have to do with  interpreting the data around a customers’ actions. But, have you thought  about the uses of predictive analytics for the opposite? If a customer  you have frequent interactions with suddenly wanes in their  communication, there may be a problem. Perhaps they’re unsatisfied with  something, or worse, they are thinking of severing business ties. Best  case scenario, you realize their lack of action early enough to reach out to them and save the relationship, but you can’t know to do that without first realizing there’s a problem.
So, how do you use lack of action to your advantage?
Look back on the customers who have left you. Can you pull out any 
patterns or trends? Use those patterns to create a fall-off model. For 
example, if you notice customers tend to respond slower (or not at all) 
to your emails prior to dropping your business, you can factor that in 
to your fall-off model. Think of your fall-off model as the ying to your
 analytics yang. When you combine the patterns from fall-off with your 
sequencing data, you can start to predict whether someone is likely or 
unlikely to buy. If they’re more likely to buy, the marketing and sales 
departments can reach out to encourage the final push.
As the trend towards predictive analytics continue, the activity  management and sales forecasting of organizations will evolve to match.  As humans, we are creatures of habit. Our behavior patterns tend to  remain steady, and if you learn to read those patterns, you can vastly  improve the effects of your sales and marketing efforts. Many CRM  systems are starting to offer predictive analytics capabilities to keep  up with this trend. Infor CRM, Salesforce, and Microsoft have all introduced predictive analytics in their latest releases, and another major CRM player, SugarCRM  has one in the works. When it comes to predictive analytics, there’s no  time like the present! Use the power of your information for smarter  sales and marketing, starting now.
Looking to improve your sales and marketing efficiencies?  Technology Advisors offers a wide variety of business software solutions  to help you achieve your goals. Contact us for more information.