Customer Service is made up of the small things

Poor Customer Service ImageI recently had a customer service interaction with a SaaS service provider that left me wanting.

With this provider, we had an issue that was effecting our ability to use their programming API to provide services to our clients at SentimenTrader. The issue wasn’t one that caused us any real heartburn and wasn’t a mission critical application, but this API failing caused a little bit of embarrassment (at least to me personally) because we couldn’t deliver the best service we could to our clients.

I’ve always been a big believer in service, specifically the fact that the ‘little things’ are the things that make (and break) customer service for any organization.

When I reached out to the service provider to determine what the issue was, I was told that ‘a bug exists effecting a number of clients, you included’.  I know what it means to develop large scale software and I understand that issues arise.  Where this provider fell down in their customer service capabilities was when I asked about a resolution to the ‘bug’.

The service representative’s response was “I don’t know. Check back once or twice a month to see if there’s been a fix.”

I don’t know about you, but telling a customer to ‘check back once or twice a month to see if there’s a fixed’ is an absolutely horrible way to thing to say to say to a paying customer.  Putting the onus on a customer to ‘check in’ on an issue sets the tone that the company doesn’t value the customer.

It’s a little thing. The customer service rep may not really have thought about what they said and/or how they said it, but it makes a huge difference in how I now view that company. When I heard that response, I immediately started thinking about replacing the service this company provides me. Here we have a company making a decent revenue from us, and they – within the span of 2 minutes of conversation – alienated a customer and pushed that customer into researching other options.

Interestingly, the bug that existed was fixed within 2 days of my conversation with the customer service rep, which was a pleasant surprise, but (isn’t there always a but?) the only way I found that it was fixed was to manually test out the service. There was no communication from the company to me to inform me the bug was fixed, which is yet another little thing that doesn’t take much effort to do. Good communication is one of the things that customer service teams should do well and is another one of those ‘little things’ that can turn average customer service into great customer service.

The ‘fix’ for this service issue doesn’t just stop with the service rep. There’s a whole host of process and systems issues that need to be addressed, with most of them being small changes. If the service rep had access to a system that gave them an estimate to fix, things might have gone better. If the service rep had insight into what the ‘fix’ process looked like, they may have been able to provide a better response.

Customer service starts with little things. It doesn’t take a lot of money, fancy software platforms and expensive teams to do well. If you start small and train reps to be customer focused and communicate well, you’ll go a long way to creating pretty good service for your clients.

What can you DO with Machine Learning?

What can you do with machine learningEveryone’s talking about machine learning (ML) and Artificial Intelligence (AI) these days.  If you are a CxO or work in IT or marketing, I’d bet that you hear these terms more than you probably want to. It feels an awful lot like the early data of Big Data or Business Intelligence or the days when the “Intranet” was first making waves within organizations.

Like most new technologies (ahem…buzzwords), machine learning and AI can seem like solutions looking for problems.  While I would argue there are people / companies looking for problems to throw their experience with AI and machine learning at, there are some viable problems out there for ML/AI. That said, I still stand behind my argument that you probably don’t need machine learning…but every organization should investigate the use of ML/AI.

Rather than buy a solution and then look for a problem to through it at (like many vendors / consultants are pushing these days), its worthwhile for every company to spend some time looking at a few important areas within their businesses to see if there’s anything that ML/AI can do to help.

Below are a few examples I’ve helped organizations with over the last few years.

Areas to start investigating the use of Machine Learning

Improving/Personalizing Customer Service

Customer service is one of those areas that you either immediately think “yes…that’s a perfect place to use ML/AI” or “uh…what?”. Hopefully you fall into the former category because customer service is an ideal space for implementing machine learning and artificial intelligence to help improve service, better understand your customers and personalize interactions.  Why’s it an ideal space?  Because you have a lot of data – some of which is structured and some of which is unstructured.  What better place to start with machine learning than a place that you have a long history of data and have multiple types of data? It’s a perfect problem for a machine learning solution.

Additionally, the use of AI for things like chatbots can drive a great deal of value for your organization. In a reported described by Business Insider,  44% of consumers surveyed stated that they would use chatbots if the experience could be perfected/improved.  That’s an impressive number given that these chatbots are automated and people claim to want to speak with ‘real’ humans when contacting an organization.

Fraud Detection and Analysis

You don’t have to be a large credit card company to benefit from machine learning for fraud detection.  While those organizations do benefit greatly from implementing ML / AI systems and approaches, any organization that has large enough volumes of transactions can use various machine learning approaches to detect fraudulent activities. How much is ‘large enough’? I can’t tell you that…but if you have transactional data covering multiple years, you should have plenty of data to build an anomaly detection algorithm to see those transactions that are out of the ordinary. Fraudulent activity detection isn’t something every organization can benefit from, but it is a large area the lends itself well to machine learning approaches.

Supply Chain Management

Another area ripe for machine learning is the supply chain.  If you sell products and manage logistics, you have a great deal of data just waiting to have machine learning turned loose on it. You can find new efficiencies in your supply chain, find areas that can be improved upon and find new avenues for cost cutting as well as revenue.  The supply chain has a great deal of both structured and unstructured data as well as many different types of data that cover many different types of metadata (e.g., costs, times, production requirements, etc). The large amount of data as well as the various types of data provide an ideal base of data to apply ML techniques to better understand and manage the supply chain.

Measuring marketing ‘reach’ / brand exposure / campaign success

One of the first things that many organizations want to do with machine learning is to throw their marketing data at it to ‘do things better’.  While I find this fairly naive, I also love the enthusiasm.  Marketing and the data that marketing groups have is an ideal place for organizations to start investigating the use of ML/AI as there is generally plenty of data of varying types throughout every marketing organization. Using ML, organizations can get a better feel for who their customers are, how to reach them quicker and more effectively and how well their campaigns have performed.

Creating a better hiring process

When I was first approached by a client and asked if I could help them ‘improve their hiring process’ using machine learning, I was skeptical. I’ve always been skeptical of most hiring processes and have rarely seen an automated hiring process within HR that I would consider to be ‘good’.   I shared my concerns with them – and they agreed completely with me – so I agreed to help them build a proof of concept system that used machine learning and natural language processing to sift through resumes to fitler the ‘best’ ones to the top. Our first attempts were no better than  their existing keyword search systems but we quickly found an approach using keywords combined with other ‘flags’ that could find those types of people that this organization liked to hire and filter them to the top of the queue.

Using Machine Learning / AI during the hiring process is still a tricky concept because a human with domain experience will generally find the best candidates for a position, but ML can help filter the candidate pool.

What are you doing with machine learning?

There’s a lot of buzz about machine learning and AI these days. Most of that buzz is because of the real value that can be found with properly implemented machine learning/AI using quality data.

What cool things are you implementing with machine learning?

Links for July 7 2011

The frustrations of being “just” a customer

Customer Service By Here’s Kate on flickrI really hate being “just” a customer.

“Just” a customer is someone you force to call an 800 number to get service.

“Just” a customer is someone that has to spend 10 minutes on the phone working through the maze of the automated phone system before talking to a real person.

“Just” a customer is someone that you tell ‘sorry…you are under contract and must pay $125 to cancel before your 1 year anniversary”…..when that anniversary date is 2 days away.

“Just” a customer is someone that you really don’t care about keeping.

I hate being “just” a customer.

If you treat me like “just”a customer, you can expect me to treat you similarly.

When I call you to inquire about my service and it takes me 3 phone calls and 30 minutes of hold time, don’t expect me to be receptive to your offers to ‘increase’ my service for your  ‘one-time special offer’.

Don’t treat me like Vonage just did and make me wait on hold for 10 minutes then connect me to someone with extremely poor phone service (vonage….you ARE a phone service provider, are you not?)  and tell me that I agreed to a ‘cancellation fee’ if I cancel within a year of my order date….and my year anniversary date is in 2 days.

Don’t treat me like Legal Zoom did either. Don’t use an under-handed technique to sell me on your service. Don’t offer me 3 free months of service than automatically charge me for a year of service without informing me that an annual charge is about to be placed.  Mind you…I wanted the extra year of service….but just remind me about the charge beforehand.

Treat me like Ooma did when I called them a few weeks ago.  Answer the phone and ask me how my day is going. Answer my questions quickly, clearly and with information rather than sales speak.  (I’m now an Ooma user..and love it).

Treat me like AppSumo did when they thought I’d unsubscribed due to something they had done.  They reached out and apologized (even though it wasn’t their fault).

Treat me like “just” a customer and you’ll be one of the first companies / services I cut when I want/need to save money.

Treat me like a person and you’ll be amazed at how quickly I open my wallet and how much money I’m willing to spend with you.

Image Credit: Customer Service By Here’s Kate on flickr

CRM tools do not equal CRM

not equal
Image by holeymoon via Flickr

CRM tools do not equal CRM (yes…I know…I’ve said it twice…but it IS important).

For the geeks out there, let me spell it out for you too – CRM tools != CRM. Or perhaps if you know your FORTRAN 77 (I taught it for 3 years…ugh) – CRM tools .NE. CRM.

Ok…now that we’ve gotten that out there…let’s take a second to look at the world of CRM.

Customer Relationship Management – CRM

According to the all-knowing wikipedia, Customer Relationship Management is defined as:

Customer relationship management (CRM) is a broadly recognized, widely-implemented strategy for managing and nurturing a company’s interactions with customers, clients and sales prospects. It involves using technology to organize, automate, and synchronize business processes—principally sales activities, but also those for marketing, customer service, and technical support

Emphasis mine.

To put it more succinctly, CRM is a strategy for managing the relationship with customers using technology to automate & organize the interactions. Love it.

I’m a big fan of CRM. I think the idea has helped many organizations build stronger relationships…and CRM tools have helped drive customers away too.

A tool is a tool

Imagine you’re a project manager. Is the whole of your job wrapped up in the tool you use to manage projects? Can anyone grab a copy of Microsoft project and start managing projects?

Sure…they can build gantt charts and make schedules…but Microsoft Project is not Project Management.

The same is true for any organization using CRM tools. Sure, the tools are available and anyone can use them…but just because you use them, doesn’t mean you are actually ‘doing’ CRM.

True CRM is wrapped around strategic thought. True CRM is looking at methods to truly connect with your customer(s). True CRM requires a ‘think; do’ mentality (i.e.,  think about it first, then do it).

I’m always amazed when I see an organization using CRM without having put any real thought into the tool and the context in which the tool is used.

Let’s look at an example.

Using CRM – A Good & Bad (and worst?) Example

I’ve recently looked into getting a loan to refinance my mortgage. Our current mortgage is a 30 year fixed mortgage with a 5.875% rate. Not bad…but with rates as low as 4.5% these days, it makes sense to look at refinancing at a lower rate…and perhaps move from a 30 year note (with ~23 years left on the note) to a 15 year note. At current rates, the move to a 15 year note would keep my payments basically equivalent.

So…I decided to see what type of rates I could get. I contacted three mortgage brokers via email and got three completely different responses.

Initial Response

Broker #1 responded quickly to my initial request in a very personal and direct manner. He told me what information he would need from me and what the process would look like. He also said he’d be calling me later in the day to chat.

Broker #2 also responded quickly via phone. I happened to be busy when he called so he got my voicemail. He left a message stating that he’d call me back. I then received an email stating the same but in a very ‘automatic email’ voice. And then 5 minutes later I received another call from him. And another email similar in vein to the first. I emailed him back and told him I’d prefer that he call me later in the day. I received an automated response that was exactly the same as the first email I received. More on Broker #2 in a moment.

Broker #3 didn’t respond to my email.

Follow Up

Broker #1 called me when he said he would. We talked about my situation and what I was trying to do and he told me he’d get some quotes to me via email later in the day. About 20 minutes after the call, I received a nice email from the broker thanking me for the time on the phone and reiterating what we spoke about. This email was obviously from a CRM tool but was personalized to me and our conversation.

Broker #2 called me later in the day and put the full force sales pitch on me. This guy is the guy you think about when you think of a salesman. You know the guy…he doesn’t listen, cuts you off and just generally makes an ass of himself. After 15 minutes of him telling me how good he is, he told me he’d get me a few quotes for new loan options.

Broker #3 never called.

Follow Through

I received the quotes from Broker #1 and Broker #2. They were basically the same in terms of rates. I told them both that I’d need a few days to look them over and think about what I wanted to do.

Broker #1 responded to my email with a “thanks…let me know how you want to proceed.”

Broker #2 responded to my email with another canned response.

Over the next 2 days, I received 3 emails and 2 phone calls from Broker #2. Each email was the same and the phone calls were received at the same time of the day.

I finally called Broker #3. BTW – some background on this broker….they are all over the airwaves in Dallas about being DFW’s #1 mortgage broker. When I called them….I got a person on the phone who couldn’t answer any of my questions, didn’t seem interested in talking to me and when I asked if I could use a system online to fill out any forms he said yes…he would email me the info. I received an email from him the following day with a PDF attached asking me to fill out the information and fax it back.


Its been 2 weeks since that first email to the three brokers. I’ve decided not to do anything just yet (we are thinking about moving next year and it doesn’t make financial sense to spend the money to refinance right now).

Broker #1 took the news in stride and said ‘call me when you want me to help with the new mortgage’.

Broker #2 didn’t respond directly but continued to send me canned emails generated from his CRM tool. These emails tell me what a great service he offers, what low rates I can get and how much he values his customers.

Broker #3 just called me back. 4 phone calls in 4 hours. Yikes.

So…the point of my story?

Broker #1 used a CRM tool…but he had a strategy for using it. It was a tool to allow him to manage the relationship.  He will get my business in the future.  If you need a mortgage in Texas…definitely call Brian Palmer at Pinnacle Financial Group at 972-529-6845.

Broker #2 used a CRM tool…but he saw it more as an advertising and marketing tool to ‘blast’ his customers. He hasn’t figured out that CRM is concerned with the relationship.

Broker #3 is an idiot, obviously.

In Closing

CRM, like most other things in life, requires some thought be put into the approach.  Just because you are using a CRM tool, doesn’t mean you are managing the customer relationship…it could just mean you are pissing off your potential customers.

Take a page from Broker #1’s playbook…figure out how you want to interact with your customers then implement a CRM strategy & platform to meet your needs.

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Open Leadership – Book review

Open Leadership by Charlene LiI grabbed a copy of Open Leadership: How Social Technology Can Transform the Way You Lead (affiliate link) by Charlene Li for my business trip last week.  Gotta have something to read on the plane you know.

I enjoyed this book.  Not only is the subject matter interesting, but the way in which Li presents the material is fresh, interesting and engaging.

The main premise of the book is that in order for organizations to use social tools and technology, they need to be able to operate in a more open manner.

I do have to say that when I first saw the title “Open Leadership”, I was perplexed. I thought that Li had somehow decided to move away from her area of experience and expertise in the social space and move into the realm of ‘leadership’ books.  The subtitle helped assuage that fear though and after opening the book and starting to read, I realized that the title made perfect sense.

In this book, Li declares open leadership to be a vital factor in whether an organization succeeds using social media.     She argues that by becoming more open, organizations will be able to build real / honest relationships with their employees, clients and vendors.

This is a good thing.  Building long-lasting and valuable relationships with people (whether they are clients or employees) is the entire reason for moving into the social space.  Having a culture of openness within an organization helps tremendously with building those relationships.

Li argues that the old ‘command and control’ structure that most organizations have used (and still use) will not work in this more open environment.  While this argument is made fairly successfully, there are many places in the book where Li tries to assuage those who still prefer the top-down command approach with her ‘controlled’ open-ness approach. When I first ran across the idea of a controlled ‘open’ environment as Li discusses, I was a little disturbed, but after thinking about it and reading more, I realized that Li wasn’t really advocating for continuing the command and control approach; she’s arguing for processes that help shape the open environment.  As long-time readers of this blog know, I’m all for processes as long as they don’t hinder the ability of the business to be ‘human’.

I highly recommend this book to anyone interested in social media, social technologies, customer service and marketing.  There are a lot of really great stories & case studies that highlight how organizations are using social media to get closer to their customers and the problems those customers are having.

If you liked Groundswell: Winning in a World Transformed by Social Technologies (affiliate link), a great book in its own right, you’ll like this book too.

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