Wish you had a magic crystal ball that would give you access to all the elusive customer information you've been seeking?
You're not alone.
In order to sell their products, goods or services, businesses need to know their target market. More specifically, they need to know what it is their customer is looking for and come up with a way to meet that need (and market the fact that they can meet that need).
Datamine has decades of collective experience diving into customer data to deliver organisations the insights they require to improve their customer targeting and drive business growth. Our clients often come to us asking the following questions - our team of experts sat down and compiled the following answers, giving you everything you need to know about customer insight.
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You won’t be surprised to hear that this is one of the most common business challenges we encounter at Datamine, and that the vast majority of the analytics solutions we offer are ultimately designed to help clients better understand their customers. Customer insight analytics are no longer a novelty expenditure – understanding your consumers’ needs and wants is imperative to keeping your organisation afloat in the ever-tumultuous waters of today’s market.
To begin, what is customer insight?
Customer insight is more than just knowing the average age, gender or location of your customers, or whether or not they enjoy doing business with you. Yes, this surface-level view is all a part of it, but analytical customer insight dives much deeper. It comes from combining a variety of different data sources (see fig. 1) to paint a rounded picture of the thousands or millions of people that make your business tick.
When done correctly, any kind of customer insight analysis should be actionable enough to affect change throughout your organisation. It should ultimately drive your company’s philosophy and decision-making process from top to bottom, giving the business the direction it needs to thrive and be customer-centric.
So how do I get those customer insights?
The first step is ensuring there is internal alignment about the project – if there isn’t transparency throughout the process, there’s a chance you’ll ultimately be unable to implement the insights. The next step is establishing a customer insights team – this might be comprised of in-house or third-party members who have collective knowledge in the following disciplines:
- Database design
- Data modelling
- Data analysis
- Campaign analysis
- Systems support
- Marketing research
- Database marketing
That team will then need to create a framework for the analysis, asking questions such as:
- What’s the goal of this organisation?
- What data do we have?
- What do we already know about our customers?
Analytics projects to help with customer insight
There are a wide range of foundational analytics initiatives that can help businesses better understand and market to their customers. Here are some of them, which you can read more about on Datamine’s Services page:
- Single customer view: This pinpointed ‘profile’ of a customer empowers you to better target and personalise future campaigns and interactions
- Customer knowledge discovery: This is an overarching analysis of a customer base that allows you to profile customers and identify trends
- Customer segmentation: The first step of marketing personalisation, segmentation divides your customer base into similar groups to enable multi-armed marketing campaigns
- Customer churn analysis: This analysis helps you determine why certain customers are churning, allows you to predict future churn and helps identify ways to reduce churn levels
- Customer acquisition analysis: Using data from your existing customer base, identify the highest-value new customers to target and the best channels through which to do this
- Loyalty programme evaluation: Analyse the effectiveness of your loyalty programme – determine potential ways to better deliver value to high-value customers while keeping overhead costs low
These are just a few of the many different ways businesses can gain invaluable customer insights through analytics.
What’s the takeaway?
Getting deeper insight into your customer base is not a one-stop process – it’s an ongoing journey to understand your customer that requires philosophical alignment within the business and a dedication to implementing data-driven insights. And the analytics solutions listed above are the first step on that journey.
One bad Yelp review can rot the whole barrel.
Reviewing a business online is easier than ever – it takes two minutes or less to log on, write up a comment, click a number of stars and press Enter. This kind of easy review can be either instrumental or detrimental to companies, depending on how people feel about their experience.
Despite the ease with which a customer can obliterate an organisation’s reputation online, customer service is still seen as relatively insignificant by many businesses. In fact, according to research from SuperOffice (U.S.), only 48% of companies respond to customer service emails! If you’re reading this, though, your business is clearly interested in delivering the best possible customer experience – as you should be. But how?
To begin, there are a number of best-practice policies that might make sense to put in place:
1. Hire friendly people: Person-to-person interactions are what truly make or break an experience with a brand, so make sure that your customer-facing team is the best of the best
2. Fix your mistakes: If something does go wrong and a customer is unhappy, do everything in your power to rectify the error and make them feel that they’re valued as an individual, not just as a wallet
3. Keep things efficient: Identify and fix areas where things are moving slow and affecting customer wait times, or where a section of your website isn’t working, or where orders are being mixed up. Find the weak links. If you don’t, your customers will
4. Be responsive: Interact with your customers online. People like to feel like they’re dealing with other people, not faceless corporations and impersonal entities. When you respond to their queries, do so in a timely fashion – the average email response time for customer service submissions is 12 hours. Be one of the companies that breaks this mould
5. Be the best: ‘The best’ has many different interpretations. Find one way to make your company stand out among your competitors – maybe have the friendliest staff? The most affordable product? The funniest social media account? The shortest wait time? Find and fixate on something that you can be the best at and use it to your advantage
6. Create a method for customer review: People are likely going to take it upon themselves to write either positive or negative reviews online. However, you can also implement ways to query them yourself – such as HappyOrNot buttons, or one-click follow up emails after a customer service interaction. Getting this feedback directly from customers will cut out the middle-man (Yelp etc.) and allow you to proactively determine areas for improvement
These are all practical approaches to ensuring a great surface-level customer experience. However, a great deal of customer satisfaction comes not only from the in-store or service experience, but from the marketing leading up to the moment of purchase. And this is much harder to perfect and measure.
In order to truly ensure a consistently good experience to your wide range of different customers, you’ll need to dive into the customer data – both to deliver that experience through your initial marketing and to measure its success. There are a number of different analytics projects that can bring you these insights, but the most common one is customer segmentation.
What is customer segmentation?
Segmenting your customer base (whether by age, location, gender, buying patterns etc.) is a great way to determine who is looking to get what out of your business. Everyone has different reasons for spending money at a company, and it’s important to differentiate your marketing between individual customers in order to deliver them the experience they’re looking for.
For example, let’s say you run a boutique jewellery and watch store. You’ll have a wide variety of customers, such as the following:
- Women who want to buy themselves fancy jewellery
- Men who want to buy themselves watches
- Couples looking for engagement rings
- Men looking to buy jewellery for the women in their lives
- Women looking to buy watches for the men in their lives
Within these segments of very differently driven customers, you’ll have to throw in the variations caused by age, location, marital status etc. Segments can quickly hit double digits!
Now imagine trying to use a blanket approach to ensure all these customers want to do business with you. Hint: it won’t work. If you show an ad or send out an email to all the segments depicting a man proposing to his partner with one of your engagement rings, it will be irrelevant for the majority of your customer base.
However, if you segment your customers into similar groups, you can create personalised marketing messages and experiences for each of them. This enables better targeted marketing spend and will show your customers that you’re paying attention to their buying habits – you know what they want, and you’re not going to spam them with promotions and ads that aren’t relevant to them.
The best way to ensure a great customer experience? Create one that’s tailored to each specific person through customer analytics.*
So you’ve worked hard - you’ve done your research, marketed well, gone out and acquired a ton of customers. This is a massive achievement! It doesn’t mean, though, that if you now sit back and relax for a few years, your customers will happily continue buying from you.
Customer churn is real. It’s an unavoidable plague upon all kinds of businesses, and it can cause anyone’s downfall if not properly attended to. So what can organisations do to lower their customer churn?
To begin, there are some qualitative business changes you can implement that will help increase the likelihood that your customers will continue to buy from you:
1. Make sure you are meeting customer expectations: Whether this means ensuring the quality of the actual product you offer or improving your customer service, make sure that what you’re giving your customers is above and beyond their expectations
2. Similarly, actually offer them the value they want: If you don’t, one of your competitors will. This value could also come in many different forms depending on what it is you’re selling - figure out what it is your customers want, and make it easy for them to access
3. Be transparent: People are becoming increasingly concerned by what goes on behind a business’ closed doors - so make yours out of glass. Be honest and upfront with your customers, and admit when mistakes have been made
4. Find your competitors’ weakness and use it to your advantage: Or if you don’t feel like throwing shade, find your unique selling point, the thing that sets your product or service apart from everyone else’s, and really highlight it. If one of your customers was considering leaving your business, what is the thing about your business/product that might make them stop and decide to stay?
5. Stay with the times: Keep improving, keep updating, keep releasing new versions of your product. You want to stay on your customers’ radar through press releases and product updates and marketing campaigns. Out of sight, out of mind - and out of business if you’re not careful
6. Implement a loyalty programme: Whether this is an enterprise-level online loyalty programme or simply a ‘Buy nine coffees get the 10th free’ punch card, putting this sort of scheme in place will incentivise your customers to keep buying from you over time. Always be looking for ways to make customers more loyal to your brand
Considering and actioning the above suggestions is a good starting point for businesses that want to lower churn. The next step along the path - the one that will really move the needle on your churn rates - is to dive into customer data to identify potential churners before they’ve actually cut the cord.
Particularly in naturally high-churn industries like Retail and FMCG, this analysis is necessary to implementing preventative measures and lowering churn on a large scale. The solution we tend to suggest for our clients in these industries is known as slider modelling - it’s an approach that looks at transactional history to identify customers that are sliding (meaning they’re close to churning). Determining who these customers are before they have actually stopped buying your product or service allows the marketing or sales team to step in and find a way to bring them back into the fold.
But my business and customers are unique - how do I do this?
Naturally, everyone’s buying patterns look different. Some people might shop at your store every couple of days, spending a fairly small amount. Others might shop sporadically and spend large amounts. By creating a model that uses previous data outlining purchase patterns and whether or not they led to churn, then running your current data through that model, you can pinpoint any customers that fit the mould of a potential churner.
The short answer to the original question is this: You can’t completely stop your customers from churning. There will always be people who will choose to leave for reasons out of your control. However, there are best practices you can implement to increase customer satisfaction with your brand, as well as preventative measures you can employ in order to catch churners before they’re gone.
Similarly to the above section on churn, customer loyalty is a difficult challenge that many organisations struggle to quantify. If you run a smaller business, chances are you’ll see repeat customers and can gauge loyalty simply on the number of returning patrons you have over time. However, the bigger your business is, the more challenging it becomes to judge whether or not your brand and service are good enough to build a loyal group of customers.
Benefits of customer loyalty
As you might imagine, there are some tangible benefits to having a consistently loyal customer base as opposed to seeing a wave of fresh customers every day (although that isn’t necessarily a bad thing):
- Those customers will be advocates for your brand: According to LinkedIn research, 92% of customers trust peer recommendations over advertising
- Loyal customers bring in more revenue: Repeat business means more regular cashflow
- There will be cross sell/upsell opportunities: If you build a strong relationship with customers, they’ll likely be more responsive to cross and upsell opportunities than a one-time customer would be
- You can lower marketing costs: Get a solid base of returning customers, and your marketing department won’t have the burden of trying to bring in an entire business’ worth of new leads every day. They’ll be able to focus on new high value leads, knowing the company has enough business from loyal customers to stay in the black
- They’ll give you useful feedback: Helpful feedback from a customer that loves your brand is much more useful (and tends to be more constructive) than a Yelp review from a one-time buyer. Implement this feedback and your customers will know they’re valued
What are some ways to make customers loyal?
Well, many of them are similar to the descriptions above for reducing churn. You need to facilitate a great customer experience and offer people what they actually want. Be transparent and up-to-date and friendly - make sure doing business with you is easy and relaxing. If you have a small business, try to remember people by name. If you have a larger business, look into personalising marketing communications so people still feel like they matter. And one of the best ways to ensure customer devotion to your brand is by implementing a loyalty programme.
Loyalty schemes can take many different forms:
- Points programmes: Every purchase earns customers points which can then be collectively spent on your products or services
- Tiered programmes: Depending on the amount of money customers have spent over time, they get ranked and assigned a tier - the higher the tier, the better the perks (Airlines do this well)
- Membership programmes: By signing up to be a member, customers agree to receive newsletters and special discounts (Supermarkets do this well)
- Cashback programmes: If customers spend a certain amount, they’ll get a certain percentage of that spend back at the end of the month (this is fairly exclusive to banks)
- Interbrand coalitions: When someone spends money at one company, they’ll get a discount at another business (many supermarket programmes offer fuel discounts, for example)
Organisations with a loyalty programme are often unsure of the value it is actually adding - it can seem like a waste of marketing expenditure if the benefits are hard to see. The only way to actually measure the efficacy of your programme is to analyse the way it has affected customer buying behaviour and overall revenue.
Ask a retailer or an FMCG organisation what the best way to get customers in the door is, and they’ll likely say the same thing: offering discounts or promotions. The goal of these special deals is to bring in an influx of sales - not only for those discounted items, but for products across the business. Unfortunately, finding this sweet spot can be quite difficult. Many companies discount items that don’t end up promoting other spend, meaning they’re potentially losing money while the customer walks away with a basket full of half-price items.
Here are some of the best discount and promotion strategies for businesses to look into, divided by industry:
- Discounts on unwanted stock - depending on your business, you should discount things like last season’s clothes, muffins at the end of the day, older models of certain technologies etc.
- Discount one component of a two-part package - if two things are typically bought together, offer a promotion on one in the hopes that people will pay full price for the other
- Offer loyalty rewards - this incentivises loyal shoppers who are already keen to spend money at your store to continue doing so
- Don’t discount your most popular product - it might drive sales in the short term, but it could damage both your profit margins and your brand reputation
- Free shipping or free returns - customers will pay full price for the item, and you’ll pay for the shipping. For some reason, people seem to love free shipping - even if they end up paying a bit more for the product itself!
- Buy one get one half price - if you pick the right product, this deal gets stock off the shelves while not compromising margin as much as some other discount strategies might
- Enter-to-win - if someone wins the grand prize in your competition, they’re more likely to feel a connection with your brand. And those that don’t win will still be signed up to your mailing list, making it more likely that they’ll also become more loyal shoppers in the long run
- Freebies - offering free tastings is a great way to encourage people to buy that product, otherwise they might just walk by it. You can also offer other free things, like free fruit for kids (many supermarkets do this now) or even branded merchandise like pens and keychains
- Coupons - this encourages people to subscribe to your direct mail or online newsletter, and (like a loyalty programme) it encourages repeat shoppers to come back
Utilities, Telco, Insurance and Banking (Service/Contract Industries)
- Multi-account discounts - for industries that offer a contract service rather than individual products, multi-policy or account discounts work well to incentivise both sales and loyalty
- Rewards for paying upfront - Some companies offer discounts for signing up that day (Telco) or for paying for a full year of service upfront (Insurance), which serves to get customers in the door and locked into a contract
- Loyal customer discounts - if someone has been a customer for X number of years, they get a discount of X on their yearly premium or bill, again serving to incentivise loyalty
- Combination offers - many larger businesses partner with outside organisations to offer mutually beneficial discounts. For example, earning airline points for every dollar spent on a credit card
- Loyalty programmes - Many movie theatres, for example, offer rewards programmes that give movie-goers points every time they see a film
- ‘Next time’ discounts - High-cost entertainment companies with few return customers sometimes offer discounts for the next time that person might want to buy their product/service again (e.g. 20% off next skydive)
- Group discounts - Some theatres and theme parks offer slight group discounts, incentivising people to seek out these entertainment opportunities for parties and other special occasions
- Local resident discounts - Tourist attractions sometimes offer a local resident discount, meaning locals are more likely to bring their out-of-town friends and family to that attraction
While these are all great general strategies for offering discounts, the only way to determine the best discount strategy for your business (particularly in the Retail and FMCG industries) is to determine your products’ individual price elasticities. This is defined as the relationship between price and demand - your ideal products to discount are those with high demand and a low price, or medium/low demand and a high price. Check out this price elasticity article for deeper insight into this concept.
Analysing the data from past promotional campaigns can help shed insight into this, allowing you to deliver more targeted discount strategies going forward and ultimately increase revenue.
It’s tempting to want to observe your customers along their buying journey, isn’t it? See what they’re picking up, putting down, what deals they’re looking at and what products/services they avoid (depending on the nature of your business, take this as literally or figuratively as you wish). This qualitative information would be incredibly useful, but it’s impossible to get at scale.
Luckily, transactional data is not. Ultimately, your customers vote with their wallets - analysing their buying patterns can give you a picture of what they like and don’t like about your offerings.
Here are a few of the things you can do with a comprehensive customer spend analysis:
- Improve discount strategy
- Manage risk more effectively
- Execute better category management
- Enable targeted marketing
- Get greater insight into your product categorisation
- Identify ways to tweak things to increase spend
Chances are, your business has already begun (at least to some extent) delving into customer spend data looking for insights - insights that will inform your business decisions moving forward. Sometimes, though, the customer information within your databases isn’t enough to give you the truly deep understanding of them that you need to affect real change.
In these cases, it’s worthwhile to combine your customer data with external data, such as the following sources of information:
Aggregated banking data: Through combining internal company information with high-level banking data (not individual transactions/profiles), businesses can better understand their market share. Such data is great for producing robust BI reports and an even deeper spend analysis.
Mobile Location data: We've found that Telco data is useful in that it gives businesses a general sense for how people (as a whole, again on an aggregated level) move around in any given area - this is particularly valuable for advertising companies that want to know what kind of and how many people drive by a specific billboard each day.
Census information: Census data can give organisations greater knowledge of their customer demographics. Some businesses only collect certain customer information and are in need of more understanding about their target customer - Census data can help fill in the gaps.
These are just three of the many data sources that can provide an extra layer of visibility into customer demographics and behaviours. Through data commercialisation, companies can buy access to external data that will give them an even better understanding of their customers and business as a whole.
Spend data, as described above, can show you (with relative clarity) how your customers have behaved in the past - what they’ve purchased, when, where and along with what else. The key to really maximising revenue and minimising waste, though, is to be able to use past transactional data to determine future output and sales.
Forecasting customer behaviour is integral to avoiding either overestimating or underestimating sales, both of which can have massively negative impacts on the bottom line.
Overestimating sales can lead to the following:
- High wastage
- Having to discount unsold stock
- Having to pay for the storage of unsold stock
- The cost of paying staff that ended up not being needed
Conversely, underestimating sales can end poorly as well:
- You lose out on potential profit without enough stock
- You damage your brand or lose customers due to lack of stock
- You lose staff who are overworked due to unforeseen demand
So how do I forecast customer spend?
There are many different ways to forecast future customer behaviour and spend. The easiest (though riskiest) way to do this is manually - if you run a small business and you have repeat customers with predictable spending habits, chances are you can whip up some kind of spreadsheet outlining approximately how much product you’ll need on a given day. Here are some simple steps to forecasting yourself:
- Determine what factors influence customer behaviour, sales and demand
- Decide which ones are the most important to monitor and record
- Decide how frequently you are going to record that information
- Record the information and track it over time
- Determine the degree of accuracy you need
- Determine the variability of your sales figures
- Determine the number of factors and levels within each sales figure
- Calculate the mean levels of your factor
- Identify factors in which there are obvious differences, contrasts and/or anomalies
- Use this information to see what is influencing demand most and focus your attention accordingly
As mentioned previously, this methodology doesn’t come without its risks - self-calculated forecasts tend to be imprecise for a few reasons. To begin, you’ve only determined and measured a few factors - there might be many more you haven’t considered. Beyond that, you’re only looking at a couple variables at a time and not fully taking into account the possible interactions between them. Finally, and most importantly, your original data may not be as accurate as you assume it to be. Is the data spread across multiple databases? Are there anomalies that could be impacting the calculations?
The moment your data becomes too big or complex for the above methodology, you run the risk of either over or under-producing and thereby impacting your bottom line. This is when a forecasting application or statistical model can come in handy.
What forecasting tools are available?
As you might imagine, there are many options to choose from, depending on the size and nature of your business. Many smaller companies use easier, less expensive tools to do their simple forecasting - these options are great for organisations that don’t have massive forecasting needs or a tonne of data to sift through, though they don’t scale well if the organisation has ambitions of grandeur.
On the other side of the coin, there are a number of enterprise-level applications available on the market for larger businesses. You’ve probably heard of tools like Oracle and SAS - hugely scalable tools with an impressive amount of configurability, perfect for large corporations or businesses with enormous amounts of customer spend to sift through. They can, though, be a bit too complex and expensive for some businesses. If that’s the case for you, check out Datamine’s fit-for-purpose forecasting tool WeekAhead, made for businesses that fall somewhere between these two extremes.
Our suggestion for getting started with forecasting is to begin with trying it out yourself - use the steps above to give it a shot, and if you find that you need a bit more structure, pop your data into a simple Excel tool. If those methods still aren’t giving you the results you desire, book a consultation with some forecasting application providers (like SAS or Oracle) and explain what you’re trying to achieve and what your limitations are. From there, you’ll have a better idea of the type of tool you’ll need in order to best predict future customer spend behaviour, and thereby sales.
For more information about business forecasting or how WeekAhead could help streamline it for your organisation, fill out this business challenge questionnaire to schedule a free phone consultation with one of our expert consultants.
CUSTOMER INSIGHTS AND ANALYTICS
Gaining insight into your customer base goes hand-in-hand with data analysis. Trying to make the move to a customer-centric business model but not sure where to start? Download the Datamine Guide to Customer Insights to the left.
Check out the business challenge questionnaire below that outlines some of the common issues we help our clients work through, and get in touch with us if you’re ready to go beyond guesswork.