Adding “A P” to the Marketing Mix

One would think that running a business is easy – just maximise revenue and minimise costs! However, this simple formula is incomplete without the essence of what makes your business unique – it’s not just about the product, but also about the price, the place and the positioning. These “4 P’s” were coined by Neil Borden in 1964 as he illustrated how companies can use marketing and advertising to generate revenues. We add two more letters to this – “Analytics” and “People”. Holistically, this new mix now centres around customer experience, ensuring that any activity of the business is firmly centred around the customer and underpinned by data and analytics. Product and Customer Experience Products (or solutions in a B2B context) can be thought of as solutions to a problem. Do you know what problems your customers face? Is your solution the right fit to solve that problem? By solving a problem, you not only meet a basic need but also open up avenues to prevent the problem from recurring in the future -this value-enhancing activity attracts and keeps customers to your brand. This is where most data scientists spend their time – building models that predict customer take-up rates and churn rates. A question I will leave you with: if all companies are building these models, what’s next? Price and Customer Experience Pricing is tricky – it’s moved away from the cold mathematics of finding the optimal monetary amount where your revenue exceeds your cost as customers want to get value from what they purchase. Prices are simply the intersection of supply and demand and unfortunately can have an extreme impact on perceived value. For example, a bottle of water at either R1 or R100 would raise eyebrows (for different reasons), indicative that people intuitively place a value on the goods and services that they purchase. Value is also driven by quality – one would expect to pay a higher price for a higher quality product or service. At the very least, you should be able to price your products and services at the point where you have a positive margin, while still maintaining a competitive edge. However, the business that will succeed combines this optimisation with what the customer expects and perceives. Do customers feel that they get value for money after purchasing from you? This value doesn’t only have to be in the price – a simple “thank you” or confirmation of the good purchase decision or tips on how to use the product or service effectively goes a long way in creating value. Data drawn from research generate valuable insights into “segmenting” your customers into smaller, more tangible groups, after which you can apply different treatment strategies to ensure that each group is at its optimal. Place and Customer Experience As we have learnt with lockdown, businesses limited by geographical location face dire consequences if their clientele cannot reach them. This was actually an opportunity to innovate, by assessing whether your products and services can generate the same appeal virtually. Naturally, this is a trial and error experiment with many as some customers may simply not be digitally inclined whereas some products can “never” be sold online. This rise in digitalisation of businesses also generated significantly more data for use. The use of digital and geographic data is currently on the rise, as more businesses see the value of placement in offering enhanced interactions with their customers. Imagine a world where your route in the mall is “laid out” for you based on your previous purchase history, hobbies and interests Promotion and Customer Experience Marketing, in a post POPIA world, is no longer about spamming potential customers. It’s about gaining trust with your existing customers by only communicating what is relevant and timely. For prospective customers, your brand and corresponding advertising also need to be targeted at who you wish to attract. To determine your existing and potential clientele, it helps to not only segment your customers but also combine their psychographic data (values, needs, wants, aspirations) with their interactions and purchasing history. People and Customer Experience It is naturally important to focus on delivering on what the customer wants, but an often overlooked factor is ensuring that you have the right people to execute on that promise. Irrespective of the size of your business, your business is unique – it has a DNA, a culture, values and principles that differ from any other. Finding others who are aligned to this experience is critical to ensure success – it never ends well to hire a salesperson who hates talking to people! How do you know you have the right people? While interviews and personality traits can inform you of who to choose, you as the entrepreneur must know what your business’s DNA looks like. Getting these 5P’s is by itself not a winning recipe. However, by focusing on putting your customers (and employees) first, it can certainly get you into the competition. How far you progress through it depends on how capable and changeable you are. About the Author Professor Yudhvir Seetharam Head of Analytics: Insights and Research FNB

Vanity, Sanity, Reality: What’s Really Important for Your Data Strategy

By Jason Foster – Founder & Chief Executive, Cynozure Group (USA) Revenue = Vanity One of the biggest mistakes is to focus on your company’s top line: revenue. Oh the allure of revenue! It’s easy to focus on the revenue number as it’s the biggest one on the P&L and it hasn’t yet been reduced by the various business costs and expenses. It’s an impressive sounding number too “we’ve grown our revenue by x% this year” can sound great. Also, it’s relatively easy to understand as it’s money into the business, it’s transactional, so there are minimal calculations to do. It is however, a vanity metric because it doesn’t come with any context. That context being how it compares to previous years, how it compares to the market, but most importantly: whether it generated any profit for the business. If you made £1m but it cost you £1.5m do so, then you’ve made a loss and have no money to reinvest in the business to drive growth. Revenue growth is important of course as its the way you will create more value in the business in the future, assuming subsequent profits. Profit = Sanity To that end the saying continues, profit is sanity. Profit is essentially what is left once you’ve subtracted all the various costs and expenses of the business. Profit is a much better indicator of the health of a business; and is more commonly used to gauge the valuation of a business. It’s a much better indicator of financial performance. Generating profits is what keeps you sane. The problem with profit though, is it isn’t actually real until it’s turned into actual money. So on paper you might have sold £1m of services and products, and it may have cost you £300k to deliver that revenue. Leaving you £700k of profit on paper. However, the actual receipt of that money is what’s important. Depending on payment terms and when money actually arrives that profit is just on paper. Cash = Reality That’s where this saying ends. With saying cash is reality. Actual physical money in the bank, and more importantly the flow of real cash into the business (not on paper revenue or profits), is what really makes or breaks a business. The money is there, you can see it, you can spend it, you can pay your staff, you can buy more stock, you can invest in growth. It’s the peace of mind required to keep a business grounded in reality. A positive cash flow is a really powerful indicator of a healthy business as it shows that you can generate revenue, collect the money, pay your costs and expenses and still be left with money. Cash is the lifeblood of the business. I’ve applied the same thinking the world of data, analytics and artificial intelligence to better help us understand what’s really important, and the reality. So it goes like this… AI = Vanity Like revenue there is an allure surrounding Artificial Intelligence (or any other latest technology solution). It’s the big one. It’s what people talk about and crave because it sounds impressive. “Yes we applied AI to that problem” “we’ve bought a platform that’s AI driven” “our software is an AI Driven platform for fixing the business”. To be at the forefront of innovation can be very important for you or your business and that innovation in, and of, itself can support your ambitions. It might attract funding, budgets, great talent. And whilst that is great, in those instances you are essentially using it as a vanity tool. Look, vanity works in the same way making revenue works; but like revenue, AI on its own is only part of the picture and needs context. Data = Sanity So continuing the analogy data is therefore sanity. More accurately, good clean trusted data is sanity. Without this your AI, analytics and insights are nothing. The lifeblood of your organisation is data. It’s the horizontal that cuts across the end-to-end value chain of your business. It gets created in every transaction and interaction that your customers, employees, partners and stakeholders have with you. Well captured, consolidated, modelled and activated data is what allows the value and benefits of having that data to be realised, and plugged into artificially intelligent systems to drive benefit. Data, when done right, is the sanity of your business. It allows you to manage processes, operate effectively, interact with customers, assess financial performance (remember revenue, profit cash?). It has the power to transform the business. Looking after it well ensures you don’t break regulatory or other legal obligations; knowing you’re on top of data will keep you sane for sure. But here’s the thing. Data is nothing really. Like profit, it doesn’t give you anything until its turned into value. You could have the best data, the best data pipelines, platform, people to manage it and model it, but without actions being taken or change being made its just data sat in systems. Business Outcomes = Reality That’s where my saying ends: business outcomes are reality. Actual business improvement through the application of data, analytics and AI. Data products that guide decision making, and people making quicker decisions – more right, more often – to improve revenue profit cash customer service business operations environmental outcomes societal improvements That’s reality. And it’s not always positive – I can find plenty of people that are impressed with the AI created and the data held by Facebook, but I can find as many (if not more) people who judge the outcomes of that ecosystem at scale to be detrimental, if not disastrous, for the world. To summarise: What happens as an outcome to your data strategy is what really matters, what really drives improvement; and like cash really is the lifeblood of the business. Listen to the podcast here.

BI in the Moment

By Michiel van Staden, Data Analytics Lead, ABSA Leadership spend most of their day in meetings, making decisions. Operations are mostly busy doing operations, taking decisions. In the spaces between, there is hopefully some time for all to engage the relevant colleague communication platforms, decision-making. When running, we run. Every now and then we might pause to catch our breath, engage those around us. Whilst running, there are apps that feeds us relevant info on our progress as we go and on pausing, gives us just what we need to decide on the way forward. Coming from 13 years in data analytics experience across fraud prevention, credit risk and operations to digital and marketing, I’d like to talk about practical ways to feed decision-making in workplace meetings, operations, and the spaces between, with relevant information. Reports Coming From Systems Within our organisation, we have many different systems collecting information. Some of these have been developed to engage potential new customers, others to process applications. There are systems to manage accounts whilst the relationship is in good standing, and still others for when that relationship goes through challenges. Based on the relevant function, each one of these processes would generate datasets that would then be stored accordingly. Much of this does now reside on the same centralised data warehouse, but there are still nuances in terms of dataset-specific access and formatting. Often this would dictate the way reports are developed. Datasets relating to applications would for example form the basis for a sales report, often taking shape around the pieces of information that happen to have been stored. In developing this report, the temptation is often great to include as much information as available, some of which might even not be accurately captured or well understood. From this position, getting the business to actively access and use these reports is an uphill battle. Even for those very close to the relevant system process, field names as captured in the data can be totally unfamiliar, whilst in parallel they are still struggling with navigating the reporting tool and trying to make sense of the overwhelming amount of information. Already being pressed for time, this does not bode well for adoption, but with time it is possible to get there. Demand is there to track business performance, and thus leadership is forced in a sense to make the reports work. As stakeholders continue to engage with the reports, questions do emerge around the fringes.  For example, enquiring what role prospecting to potential new customers played in sales and what happened with the relationship post sale. At this stage there might very well already be prospecting and existing customer relationship reports. In some cases, the data specialist responsible for sales reporting might also be close to those, but more probably not. Whether to merge these reports or keep them running in parallel, with the increasing likelihood of overlaps as they grow, can be a very complicated problem to solve. Can the different data sources be compiled practically into one report? Are the other reports being used? Will the overlapping numbers be consistent or conflicting? When not handled well, you can easily end up with a myriad of reports, containing duplication and inconsistencies, whilst becoming increasingly too large, complex, and unwieldy to be of any practical use. Add to this ad hoc requests for specific pieces of information increasingly landing on data specialists laps because stakeholders are not able to effectively find the information themselves. The Business Does Not Know What it Needs When you do ask the business what intelligence they need, they are not able to tell you.  Not having a view of what is possible and available in terms of reporting makes it very difficult to devise specific requirements for what the business will need and be able to practically use. As data specialists, our first task is to get to know the data on offer very well. We have to figure out how to access the data coming from different systems, need to ask the questions towards understanding exactly what each piece of information means and ultimately need to become very comfortable in weaving data from these different sources together into an end-to-end picture. Additionally, it is also key to understand the business. What is the business strategy? How does it make its money? What are the key processes? What does the business offer its customers? And lastly, take time to listen to and understand your audience. What does their typical day look like? What challenges are they facing? How do they make decisions?  What are their thoughts around data? How comfortable are they in working with data? Only once you’ve got a very clear understanding of all of these components can you engage your stakeholders very practically, giving them the business intelligence they need to do their jobs better and make informed decisions. BI in the Moment Knowing exactly what data is available and which processes are core to the specific business area, sit with your key audience to understand what the key meetings are in their schedules and unpack what information would better enable them to make the critical decisions in those sessions. Give them what they need. Also spend time in the various operational functions. Unpack what systems they are using and how they make decisions within those processes on a day to day basis. Give them what they need. Understand your data Understand your business Understand your audience Give them what they need In the spaces between there might still be additional, maybe slightly more generic information that could give your audience the latest on business progress or performance, informing their decision-making more holistically. Actively work with your stakeholders towards narrowing down a handful of key metrics, giving them what they need at a glance, in an email or messaging body. Clicking through to reports on a daily basis quickly becomes very tedious and discouraging. Before adding any new metrics or views to a dashboard, review all the existing ones. Are they still relevant and value adding? Or is the report starting to slide into becoming less valuable?  Then something has got to give. Nobody wants to keep generating reports nobody uses, and nobody wants to be inundated with reports they cannot use. Give them what they need. BI in the moment.

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