#1 Maybe let’s start by having you give us the data-lover’s perspective about analytics. Morgan, Why do you love it so much? (1:45)
#2 Can you give us some examples of taking data to make data and how that helps lead to decision making and uncovering stories? (3:30)
#3 One of the things I liked about your tools was that you could just isolate a few of the stories we’re interested in such as loyalty reports, product reports, and behavioral search. Tell us about some of those modules and what insights are gained from those? (5:15)
#4 What other modules do you have? What kind of data does it capture and what can you do with it? (8:15)
#5 I might add that your software is compatible with most point of sale (POS) systems such as POSIM, Shopify and even Like Sew which I know a lot of our clients are running. What additional information does Impact Analytics provide that a POS doesn’t? (9:50)
#6 If you’re listening to this show thinking, “All I see is a jumbled mess of stuff that makes no sense to me.” Where do you advise that people start to make the data work for them? (11:50)
#7 I run a mastermind group for retail owners and last week one of the members’ challenge for the group was how to do better tracking of success in her shop. She said she has good sales days and sometimes really great sales days but then has a hard time tracking what led to that. Do you have any advice for her? (14:40)
#8 I’m interested in how the analytics can inform our marketing strategies so let’s dig into that a little bit. Give us an example of how one piece of data can be analyzed into knowledge that becomes a marketing advantage? (16:55)
#9 How often do you recommend listeners look at their numbers? (22:08)
#10 Do you have metrics that you think are the most important for retailers to keep an eye on? (24:45)
#11 Does your platform have the ability to utilize predictive methods of analysis? Maybe start by describing the difference between predictive and descriptive analytics first. (28:40)
#12 If the input quality of data is flawed and erroneous, the output can never be reliable. How can you be sure that what you’re collecting is actually going to be useful? (33:00)
#13 I know that my audience is extremely visually oriented. Is there a way that the data can be presented in a visual manner that helps with interpreting the story there? (34:38)
#14 Most companies can’t afford an IT person to extract data and then communicate with a marketing team to make the best use of the data. How do you advise that companies overcome that lack of trained staff in those roles? (36:15)
#15 We should let listeners know that we’re working on a partnership whereby you set up our clients with the ability to extract data into monthly reports and then our team will do the analytics and make marketing recommendations to get better ROI. Can you say more about what you’re excited about with that new venture? (37:50)
