How KYC (knowing your customer) & KYE (knowing your employees) can help you make smarter, quicker & better decisions.
Most businesses are sat on a goldmine and, if they tapped into it, they could make more money…but they don’t. The goldmine is data…and data could include customer records, financial transactions, employee records, website behaviour, marketing responses…any type of data.
Data can be used to make your business money in two ways…
- Knowing your customers — making data-informed decisions so you can acquire, develop & retain customers faster & better than ever before, driving higher revenue at lower costs
- Knowing your employees — making data-informed decisions so you can recruit, develop & retain talent better than ever before, so your business is more successful
KYC — imagine if knowing your customers powered your business performance…
Most businesses have loads of data on their customers. Often data is sat in different locations, in different formats and with different people…but businesses often have a goldmine of customer data when they dive into it.
Imagine if you could…
- Identify who your most valuable customers are so you could target more customers like them in future
- Identify, in advance, when a customer might leave you, so you can intercept and apply preventative measures to retain them
- Calculate your cost per acquisition across your sales channels so you can adapt your sales and marketing activity
- Segment your customers, understand their value and design specific products and services to match their needs
- Predict how customers will behave in future so you can make decisions now to maximise your business opportunities
You can do all of this, and more, with data. Knowing your customers helps businesses make smarter decisions on their product, price, marketing, sales & distribution strategies.
KYE — imagine if knowing your employees powered your business performance…
Most businesses have loads of data on their employees. Again, employee data is often sat in different locations, in different formats and with different people…but you will often find businesses have a goldmine of employee data when they dive into it.
Imagine if you could…
- Measure the effectiveness of your recruitment activity in terms of speed, drop-outs and cost per recruit
- Analyse how performance and engagement varies across your business lines, job families and locations
- Assess how well your employee benefits & reward schemes are working by business line, job family and location
- Understand employee behaviour, capability and diversity
- Forecast future employee trends so you can make decisions now to maximise business benefits.
- You can do all of this, and more, with data. Knowing your employees helps businesses make smarter decisions on their recruitment, reward and retention strategies.
So where do you start?
Most businesses have common data challenges…
- They lack data resources in-house because their data teams are too busy with BAU tasks. They don’t have the time to explore data opportunities.
- They lack data skills in-house, as you need a combination of data consultancy, data analysis, data science, data visualisation & customer insight skills in a project. These data skills are in high demand.
- They lack the ability to monetise or commercialise data opportunities in-house because they haven’t done this before.
What’s the solution?
If your business is caught with one of the three problems above, your options are to hire in a combination of data consultants, analysers and visualisers, or hire an agency to swoop in and do it all for you. Whichever route you choose, it’s best to follow a process when completing a data project.
- First off, identify the business questions that you want answered. What would help your business to perform better? What business levers of cost/revenue can you influence?
- Extract the data that you need to answer the business questions. You need the Goldilocks amount of data — not too little, otherwise, you won’t be able to answer the business questions. But not too much, otherwise your data tools will be slow and cumbersome.
- Without a doubt, once your data sets are together, you’ll find errors. So what you’ll need is a repeatable process to cleanse, enrich and combine data sources together. You’ll need to merge data sources, reformat fields and match data so it’s accurate and relevant.
- When it comes to analysing your data, you’ll need to decide which ways you’ll slice and dice it to achieve your business objectives. You can look at descriptive data, where you look at trends and patterns of the past. You can forecast data, where you use past data to predict what will happen in the future. And you can model data, to show you how changing certain scenarios will impact your business.
- Your final stage is to create interactive dashboards that can be used by your business to make smarter decisions on customer and employee strategies. To get it right, your dashboard needs to be based on your business user requirements, careful planning, engaging storyboarding and smart visual design. Another important choice to make it the type of tool you use. There are lots on the market, and they all have their pros and cons. PowerBI and Tableau are popular choices, but ultimately the best tool is the one that works best for the project in hand.
About the Author
Lee is a writer and strategic thinker, helping Data³ with all things marketing. Lee is a firm believer of using data analytics in the world of marketing, specialising in customer segmentation and bespoke copywriting.