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When I first started as a call centre trainer, I listened to a sales team leader’s briefing. Like many naturally talented salespeople, he couldn’t explain how he was so good.
He told his team to build rapport with their customers. One recent recruit asked: “How do we build rapport?” He replied: “Be yourself!”
I thought to myself: “What does that mean? There must be a way to train for this.”
I did some research on the internet and found various techniques. These are the top four which I included in the first training session of our agents’ onboarding course.
1. Use the other person’s name
Dale Carnegie said people like nothing more than the sound of their own name. Using a person’s name can get and hold their attention very effectively. Like all games, this one has rules.
Make sure you know how to pronounce it. I work with people from all over the world. I often first see their names in written form. So I will ask them, “How do I pronounce your name?” No one wants to hear someone mispronounce their name, and they will appreciate that you have taken the trouble to say it correctly.
Don’t overuse it. The classic stereotype of the “slimy sales guy” uses a customer’s name at the end of every sentence. Use the person’s name at the start of the conversation, and then at points where you want her to pay special attention. That should not be more than once or twice.
Names can be a sensitive topic. In the English-speaking world, using first names with complete strangers is considered normal. In the Czech Republic, it’s still common to use “Mr.”/“Mrs.” and a surname. Be careful to fit in with what’s normal for their culture, or you could be seen as disrespectful.
2. Question, answer, comment (QAC)
When two people talk for the first time, they often ask each other questions.
At a conference, you might ask: “What do you think of the event?”
When your partner replies, respond with a comment before asking the next question. Here’s an example:
“What do you think of the event?”
“It’s not what I expected. I was hoping there would be more presentations.”
“Really? What aspect of XYZ are you interested in?”
The comment, “Really?” shows you are interested in her answer.
Two points to note: your comment needs to be appropriate to the answer, and you should not use the same comment for every answer, otherwise, you will sound like a bored telemarketer.
3. Something in common
Finding something in common with the other person is a good rapport-building technique. If you are talking to someone, you are in the same physical or virtual environment.
You could ask a question or comment about the event you are both attending.
You could comment about the signal quality of the video conference call you are on.
If you meet face to face, you could do the classic British thing and talk about the weather!
You could also volunteer some personal information, such as mentioning your children or pets. People love to respond with a similar comment of their own. Suddenly, you find that you both have teenage sons or Jack Russell terriers. You have something in common to talk about!
This is the most effective, but the riskiest way to build rapport. Humour is usually culturally specific. What makes one person laugh could leave another person cold, or even get you a fist in the face.
I wait for the other person to make the first joke, to gauge what works for her.
If you’re going to make a joke, don’t make a joke at the expense of anyone you are talking to.
I know someone who was talking to the managing director of another company. He made a humorous comment about salespeople. The managing director had spent the first 20 years of his career in sales.
You may think that self-deprecatory humour is a safe option, but in some cultures, making jokes about yourself is seen as a sign of insecurity and weakness.
How Can I Improve My Game?
Start by watching other people and how they build rapport.
Watch what other people do in meetings or conversations. Watch TV or films where people have conversations. Police dramas are great since police officers usually try to build rapport with witnesses and suspects who they interview.
Start actively practicing by trying one technique at a time in conversations. Watch how your conversational partners react, and take that as feedback.
I used a practice activity where every new trainee had to ask the other trainees five questions to get to know each other. They had to use rapport-building techniques. Fifteen minutes after the exercise kicked off, the classroom sounded like a party!
If you go to a networking event, prepare four or five simple questions and go around the room and try to talk to everyone, using the rapport-building techniques. See how they react.
I love hearing how people get on when they use these techniques, what works for them and what doesn’t. Send me a message and let me know how you got on!
Part One: Data Strategy Is More Important than Ever in an Age of AI.
This will be a multiple-part series on data strategy and how it is the precursor to data management and data governance.
Firms often skip many essential steps to creating a data strategy favoring data lineage/governance, usually for regulatory compliance rather than creating a holistic yet integrated vision for data. While practicality is always good, it can be at the bane of getting the most out of the firm's data over time. When a data strategy does not guide data governance, this keeps data governance in a defensive position in general; it is a big mistake that keeps data governance in the basement of the organization, being perceived as a cost center and not the revenue and monetization driver that data governance can be.
Let's start with what a data strategy is and why your organization needs one. Then we will discuss in future articles how data governance needs a tighter connection to strategy.
Data strategy and how I like to think about it is a sharp vision for how your data is organized and turned into knowledge throughout the organization.
There is data, information, and knowledge. Each of these has some organization of data and planned use cases. I like this pyramid or hierarchy paradigm for data strategy. As you go higher, it's about generating insights and improving the quality of decisions based on clean fit-for-purpose quality data.
20 Key Considerations In Your Data Strategy
Some key considerations in your data strategy, and I will not prescribe the answers to these considerations here:
1) How do you define quality data?
2) Who gets to move data and to where?
3) Is there a planned level of data duplication, or is it, as they say, the "Wild West" with replication all over the place?
4) Do we want to have one version of the truth or multiple versions of the truth? What are the risks and benefits of each?
5) Are we using an ETL process or ELT in the age of big data?
6) What types of data models are we using? Logical layers (star Schemas) no SQL, blob storage?
7) Are we using open gardens or data lakes, or a pond approach?
8) How do we define our data fabric at the firm?
9) What newer tools do we use for moving data. Are we using AI-based tools (RPA, etc.)?
10) Who can access PII or NPII data, and how do we create highly secured data zones?
11) How many self-service analytics tools do we allow? Do we need both PowerBI and Tableau?
12) Do we have an on-prem cloud approach or a full-on cloud data strategy?
13) Where do AI and cognitive technologies get their data?
14) Do we have transparency in business rules and algorithms that drive our business?
15) How do we monetize our data, and at what point in the data lifecycle?
16) How many customer keys or unique identifiers do we carry?.
17) What is the role of generative AI?
18) How do we resolve the identities of both prospects and customers?
19) Who owns the data? Do we have producers and consumer-defined roles?
20) Do we have a centralized or decentralized approach to data management, and is our organization clear about how we operate?
There is no formal data strategy if the firm doesn't have clear answers to many of these questions. In addition, a data strategy is not a data management framework, which would come next once you have defined the strategy.
"Why is this important?" you ask. It will help you set the priorities for data governance and data management organizations (DMOs), rather than just having them fall into a project or two and perhaps only viewing them as the people who handle compliance issues or controls. Remember DMOs, enable data science, marketing automation, AI, CRM, and many other revenue-generating functions. An integrated enterprise data strategy will allow you to scale your data management and governance efforts, making the work more important and meaningful and increasing the focus on the business objectives and ROI.
I look forward to your thoughts on why you think the tail is often wagging the dog regarding data governance versus data strategy.
In our next issue, I will discuss master data management and data governance in detail.