It's time to solve for the last mile of the pricing optimization journey.
What just happened…?
You’ve just introduced a new campaign special out to the market. You’re super excited to see the results that your analytics or marketing teams have been telling you to expect. Technology is feeling good about the changes. The pizza party is already planned and all we need are the results…
Two months go by…results come in…3 bps lift with a modest volume increase. It’s ok…not great…not bad…the disappointment in the room is tangible. The pizza party is canceled, finger-pointing everywhere, according to everyone – no one knows what they’re doing. That didn’t seem to be the case two months ago. How did we get here?
The Last Mile Problem
Doing the post mortem, you’ve confirmed all the boxes were ticked and double checked the analytics but the final campaign results just don’t make sense.
- How can a branch two blocks away from another perform twice as well?
- Some regions sold a lot but at a discounted price?
- Why did some of our higher performing branches do so poorly on this campaign?
We finally started talking to branches. Suddenly the breakdown became clear as day.
- “The process took too long and the customer decided to not bother with it.”
- “I felt like they didn’t need the product so I didn’t bother telling them about it.”
- “I didn’t think the pricing made sense for a long-standing customer.”
- “We discussed it at length but they just weren’t interested.”
- “What campaign special?”
You may be led to believe that this is simply a case of poor change management or bad product design but this is a pervasive, persistent problem in every industry with a human front line. No matter what you do, you are still beholden to the front line’s choices. I’ve seen this happen on several (bank and non-bank) initiatives. A challenge not unique to any industry. Unfortunately, until chatbots and AI completely take over, this will not change. This is the last mile problem.
How do we solve it?
Solving a problem can only happen after understanding the problem. At most banks, you are “empowered” with the following data point: someone bought something at some price. That’s it. (Sometimes we’re lucky enough to know someone came in and bought nothing.) We know very little about the story behind this key data point.
- How long did it take to make this decision?
- What products or price points were discussed along the way?
- Who did they talk with and when?
- How streamlined are the conversations?
Only by creating transparency around the front line can we then decide the appropriate path. Many existing tools are designed to improve to make the front line and customer experience better. Not all of them aim to make you smarter.
Tips and Tricks
- Seek to understand the front-line behavior and adjust your strategies accordingly
- Engage with your front line early and regularly – it is not a one time exercise
- Change management starts from the top – make sure there is consistent and clear messaging across all layers
Thinking about ways to empower and understand your front-line?