Many businesses are having to respond quickly to the dramatic shift online, whilst making sure they adapt their offline business models to work with the 'new normal'. This is particularly true for brands in categories such as Home, Automotive and Travel where the physical store and sales agents continue to play a critical role.
This paper looks at the role data plays in optimising the digital transformation of these business models and how data can act as the glue that integrates the on and offline into a truly omni-channel customer experience.
Changing Market Dynamics
Retail ecommerce platforms have undergone an unprecedented increase in global traffic between January 2019 and June 2020, even surpassing holiday season traffic peaks. Overall, retail websites globally generated almost 22 billion visits in June 2020, up from 16.07billion visits in January 2020. (Source: Statista).
This is a substantial shift in behaviour and whilst many countries are still experiencing lockdown measures, so it could be too early to say definitively, this has huge implications for omni-channel businesses for the long term. Digital transformations have been underway for some time, but now the need is greater than ever.
Post pandemic recovery in China
By mid April 81% of retailers had reopened 100% of stores and a further 15 had reopened 90% of their stores.
Of these retailers only 75% of them were seeing footfall above 50% of pre-lockdown levels.
(Survey by Li Yang - Beijing News).
These are big numbers when you consider the economics of high street retail and that the challenge of making 'offline' work has been ongoing for most advanced ecommerce nations for some time.
In China lockdown has largely been lifted for some time and if we look to what has been happening to the traditional high street over there it provides some telling signs of what is likely to come.
For some sectors, like grocery and fashion, it is reasonable to assume that this is simply an acceleration of expected future behaviours and that some of this regular demand will have moved online for good. However for others, where the sale typically relies on physically testing out the product or requires the intervention of a knowledgeable sales person (such as Home Improvement, Furniture, Automotive and Travel), it is a clear signal towards a new long-term model.
Pre-Covid, competitor pressure was already mounting from online players like Amazon shifting into multiple categories and this was driving many transformation programmes to get the business truly omni-channel and 'performing its socks off' for todays consumer. With the pressures on traditional real estate economics, understanding customer behaviour to deliver the ultimate purchase experience across channels has become the value game changer.
For many of these retailers though, the on and offline divisions are still set up practically as two separate operating divisions. This has made integration and therefore a seamless customer experience very hard to achieve. The challenge now is to make a truly seamless omni-channel brand experience for customers happen at pace.
For these businesses this means ensuring from an operational perspective that the management and conversion journey of every lead generated, whatever the source channel, is optimised. We call this Sales Lead Optimisation. A strategic omni-channel solution that uses data to take a channel agnostic approach to converting every lead possible.
Exploring Sales Lead Optimisation
What is Sales Lead Optimisation?
Traditionally businesses have thought of optimisation as something that applies only within the digital realm. Referred to as Conversion Rate Optimisation (CRO) it has remained very much the domain of the web team and their development agency to ensure the digital channels and experience are working effectively.
However, for business that relies as much on digital as physical or human interaction to make the sale, optimising their online channel is only half of the challenge. Businesses are quite rightly demanding more from their optimisation partners.
In order to make the whole business work, they are quickly recognising the need to think omni-channel realising that the time of separate approaches to the digital and physical channels is well and truly over. Enter the fundamental shift towards an approach that looks across every channel and considers the lifecycle of a lead in its entirety.
The Role for Data Analytics
Now more than ever businesses need to explore more holistic solutions from their data analytics efforts that consider lead optimisation across the whole omni-channel environment. This means looking at everything from;
Optimising spend across relevant highly targetable media (digital and offline) to create leads where the opportunity is greatest and to play to the strengths of the retail estate.
Tracking a singular view of leads from multiple channels as they pass through and across both the on and offline channels.
Designing and developing effective multi-channel journeys and targeted experiences that follow the customer as they move backwards and forwards through researching online and into store to touch and feel the product.
Ensuring the range mix in store works locally for both off and online customers.
Maximising the lead pool value by identifying and actioning every missed opportunity across every channel.
Intelligent use of and automation to deliver targeted actions (digital or human) to drive conversion, recover abandoned baskets or cold leads.
Managing the incentive systems of the sales staff on the shop-floor and in the call centre so that they embrace a seamless experience for the customer.
Before running tests establishing the methodology by answering the following.
Where to Start with Sales Lead Optimisation?
Sales lead optimisation means starting from the very beginning and arguably the highest cost part of the customer journey is where leads are generated; the media strategy and budget. Today the media budget represents a very noticeable number on the P&L and is coming under scrutiny as the need to do more with less grows. The pressure is on for business to dramatically reshape the marketing mix.
A root and branch analysis is needed to review both the physical and digital experiences through the multiplicity of channel combinations that customers like to choose. This means tracking the customer journey all the way through and most importantly not forgetting to identify the importance of proposition factors (product, price and promotion mechanic) over technical things like page navigation and carousels.
Finally inspection and re-design of operating structures and specifically sales reward programmes are needed to ensure the experience works across digital and physical worlds and everyone is working in concert to secure the best outcomes for every lead that enters the business.
Who is Sales Lead Optimisation For?
Sales Lead Optimisation should be a priority for any business that relies heavily on the successful interplay between the physical and digital environment to create and foster a lead and then convert it into a successful sale. Many of which can be found in the Home Improvement, Automotive, Finance and Travel sectors. In particular, Sales Lead Optimisation is especially relevant for businesses that share some or all of a number of the following characteristics that pose their own challenges.
High value, low frequency purchases
These categories often experience far lower visit rates. Repeat purchase rates are also usually very low (once you have bought a new kitchen, bathroom or sofa, or car, that is often it for a very long time).
This means that for many of these brands the sales opportunity is a one-time only event that needs to be handled right to convert, or the chance is lost for several years as the customer has purchased from the competition. Therefore maximising the chance for a successful outcome when a customer displays interest in your brand might be the only shot you get.
Lower media/marketing budgets
Many of these categories are 'own brand' and as such cannot pull on collaborative marketing funds from suppliers to extend the reach and effectiveness of their marketing.
This often means lower available budgets for expensive outlays in media. As such generating leads that the business can follow up and deliver with the best chance of closing means getting the most out of tight budgets and spending across multiple channels specific to locations.
A direct consequence of the competitive nature of these categories is that promotions often play a crucial role in driving footfall and stimulating purchase.
This means that new products, marketing plays and promotions need to work hard and be readily adaptable to changing circumstances. As such the testing and optimisation of these needs to be fleet of foot, accurate and flexible to quick change and modification. This needs accurate, readily available data.
Chief Executive Officer
DFS Group PLC
“Simply optimising our digital channels was never going to be enough.
It was time to re-think our entire lead generation model as well as some fundamentals about our campaign strategy and operations if we were going to be successful.
We needed to take some brave decisions to stop doing what we had always done and use our data capability to re-think our marketing investment, re-design the customer experience and how we operate internally.
Beyond has the culture, breadth of experience and understanding of how our type of business model works to lead our data journey through this transformation to a hugely successful outcome.”
Key Challenges addressed by Sales Lead Optimisation
Infrequent customer visits
A range assortment that appeals to all customer segments (on/offline)
Targeting to optimise ROI
Often need to touch and feel the product so omni-channel approach is inevitable
Maximising profit margin through add-ons
Conversion heavily reliant on sales agent support across channels
Purchase typically requires retails finance and customer credit checks
Managing customer expectations and production forecasting
Optimise cost for final mile
Considered high ticket item purchases are less frequents as a missed lead is truly a lost sale
The products and therefore the customer decision-making process can often be more complex and therefore the customers are more reliant on more detailed product information and tailored advice from trained sales staff. Optimising sales operations to ensure the right people are in the right place to meet customer demand and enabling sales performance insights to inform and motivate teams becomes a game changer for performance.
As final product margin and company performance is often down to the sale of product upgrades and add-ons (which can be heavily reliant on these sales agent interventions) this means the sales team - in store or over the phone - are a crucial cog in the conversion cycle. Therefore, designing, developing and implementing an effective sales incentive scheme that works across channels with leads coming in from the web through to the high street and avoids the traditional ‘lead hoarding’ by agents, can be a hugely complex and sensitive issue to get right.
As much of the spend in these categories is higher value the sale can also require finance, which naturally places barriers in the way of the purchase. The application and approval process needs to work in harmony with the customer journey or it can be a massive turn-off for the customer. This raises its own challenges but also offers many great opportunities.
Delivery is often more complex, requiring more organisation that simply packing and posting. Optimising the costs to ensure delivery routes and resources for two-man lift operations are efficient as possible, whilst keeping every customer happy, can play a significant role in the final product margin.
Nicole Richardson - Partner, Beyond Analysis
Actionable data analytics sit at the heart of Sales Lead Optimisation in many different guises. Initially its role may be about providing the fact base from which the business is able to identify challenges, design new products and solutions and facilitate internal buy-in to new ways of operating.
Throughout the digital channel experience it plays a pivotal role in enabling automated, trigger-based responses along the journey to tailor the experience and content. Without it the business is unable to effectively facilitate measurement and tracking of leads to incentivise and reward sales staff to engage and ultimately support the success of a profitable omni-channel approach.
Unlike grocery, for many categories data has taken longer to find its home and prove its value. This nascence of data raises its own set of challenges for these brands that it is critical to understand and address when looking at sales lead optimisation. These businesses often have not had the luxury of highly effective loyalty cards tracking consumers and enabling targeted communications to drive data insights to help optimise the business.
This means they often lack the granular customer-level insights to use in designing their proposition and products to ensure they suit and are meeting the needs of every customer group. This is exacerbated with physical space restrictions and cost where the opportunity to display very large ranges can be limited.
Without the direct customer connection targeted communications to get the right product in front of the right customer can be very hit or miss making the sales process even harder. Consumer behaviour and technology adoption means further challenges for these brands in what to expect from their customers and the decision making process.
We have moved away from neat and tidy segments of customers that are either ‘tech savvy’ or ‘traditionalists’ with predictable behaviour traits, towards a much more homogenous blob of customers who are happy moving back and forth between channels in quite unexpected ways as they research, choose, buy and manage their purchase and delivery.
Gone are the days when it was enough to assume that a certain customer type will research online, then go instore to touch and feel the product and make the purchase. Today consumers (lockdown-aside) are behaving in anything but traditional ways.
Sales Lead Optimisation Approach
Sales Lead Optimisation is a holistic multi-channel business optimisation approach. As such it considers everything from the initial media and lead generation strategy, individual channel performance and customer tactics through to the performance incentives and operational needs of the sales teams in branch networks and call centres.
The Sales Lead Optimisation process is much like any other business problem solving and data analytics task, but it requires a much broader philosophy and approach giving consideration across channels, products, services and how the business operates or structures itself internally.
An effective engagement model can be structured around five broad phases:
Hypothesis and action planning: Taking the diagnostics and crafting these into actionable and measurable hypotheses for change and improvement to meet specific business objectives.
Prioritisation: Carefully crafting a prioritised plan of attack to implement and test changes, balancing the business priorities with technical feasibility and cost whilst maintaining a manageable environment that ensures the tests can provide meaningful and credible results.
Testing: Defining a testing approach and success criteria prior to implementation.
Results: Analysing and interpreting the results of the testing. Rather than attempting to deliver these sequentially, a flexible and agile philosophy based on delivering quick wins through manageable changes and improvements will enable improvements to be delivered in short timescales.
Diagnostics and Research
1. Understand your customer
The first step is to build a profile of customers to understand behaviours and size the commercial opportunity using meaningful groups of customers with similar needs. This could be done across a number of dimensions such as loyalty (Recency Frequency and Value), Profile Segmentations (where available such as demographics or lifestyles) and, where relevant, additional dimensions such as geography (industry vertical if dealing with B2B) and channel usage.
This allows you to create a perspective on which behavioural customer groups currently generate the best value (sales/margin), how effective current acquisition is and what the conversion rate at various stages of the journey, where drop off is happening and value is being lost. Putting the behavioural diagnostic front and centre also ensures strategies and solutions can be actioned. This value-based view will provide the focus for the subsequent, more detailed research which otherwise could be a bit like looking for a needle in a haystack.
2. Identify your true market
This is a hyper-localisation strategy to build detailed views of headroom opportunity by catchment area, geography and TV/Radio regions. The aim is to build strong predictive models that drive local marketing initiatives aimed at stealing competitive share and pin-pointing lead generation activity where the effect will be greatest.
You do this through your data partnerships by combining internal data sources with those from your finance partners to establish postcode level market share by catchment and identify the higher or lower areas propensity to convert. With this hyperlocal view you can re-define media goals and plans that are now both highly targeted and through using a smarter blend of local media (lower cost) options driving down the cost per lead significantly.
3. Identify what your visitors are doing
With a solid view on the customer base and the market potential you have the means to focus your research by groups of high potential customers and what they are doing and where value is being lost. This is the traditional Conversion Rate Optimisation approach to building an understanding of what is happening to leads as they pass through the various stage of the customer journey across your channels.
For this phase you will be looking through your acquisition traffic analytics (audiences/demographics), entry points, real-time web data tracking, bounce rates, and on-site behaviour and journeys. Using this you can formulate a view by different customer types, acquisition sources and entry point of the journey taken through the website and importantly where they drop off and move to other channels or otherwise. The outcome is to identify which routes are leading to successful outcomes and which are not and what the value loss of this is.
4. Establish where your customer are in the decision making process
Predicting where the customer is in their decision-making cycle is a key element to lead optimisation as it acts as the trigger for what the next most appropriate action should be. Many optimisation projects get very focused on pushing the customer through to a closed sale, but more often than not, particularly in sectors that require lots of pre-purchase consideration, the customer is not always ready.
In omni-channel lead optimisation the trigger means it is often time to do something completely counter-intuitive to traditional CRO – encourage the customer away from the website into store. By looking at the profile of baskets and how they have been used throughout the journey to date you can predict where they stand in the journey.
Understanding how basket and behavioural profiles differ by completion states tell you which to target, how and when. The various completion state dene the triggers and measures that distinguish between different characteristics to inform different experience routes.
For example a leading European omni-channel furnishing retailer has a number of tell-tale signs that indicate journey stage such as; the number of products in a basket (does it relate to a range or set of suitable accessories?); does the basket fit with expected norms or is there a random selection suggesting their mind is not made up yet?; have fabric choices been actively made rather than just the defaults?
All of these together provide indicative completion states that require different responses to keep the experience on point and relevant. Critically they provide the relevant triggers for when human interaction in the form of invitations to store, design calls etc. are made to help the customer through the final stage.
(See section on internal process and organisation).
5. Match the right UI/UX experience with your customer
A range of analysis tools such as session recordings, heatmaps, and site tagging are readily available to build a comprehensive understanding of how your customers are behaving on your digital properties and where blockages or issues are happening. Where available also look to incorporate the feedback from customer surveys, feedback sites and NPS results to provide more context as well as pick up on areas that customers are telling us about directly.
Where possible conduct qualitative research as this can provide the important narrative around the ‘why’ of consumer behaviour. However, always carry out and exhaust all quantitative sources first, using qualitative interviews or surveys to enrich and contextualise the behavioural findings.
Unless the qualitative research can be tied back to actual behaviour of specific customer types it carries little actionable value in the context of specific CRO initiatives and it is therefore best to leverage existing qualitative research that has probably already been done by the brand team.
6. Target the right product or service proposition
This is about understanding the basics around how different customer types respond to a proposition. For a call to action or optimised site journey to work, so must the overall proposition. Fixing the navigation or re-designing the user interface won’t make a difference if the wrong product or deal is displayed. Build a view on the preferences and propensities of each customer groups around;
Price sensitivity and whereabouts in the range architecture they are likely to shop most (e.g. good, better, best);
What features of the product or service they respond best to;
What promotional mechanics or offers are they most suited to.
This work, particularly store ranging, needs to be aligned with the hyper-local media strategy and considered across the physical retail estate, especially for businesses in sectors such as Home and DIY where a store visit is a likely part of the purchase journey. This is a hyper-localisation strategy to build detailed views of headroom opportunity by catchment area, geography and TV/Radio regions. The aim is to build strong predictive models that drive local marketing initiatives aimed at stealing competitive share and pin-pointing lead generation activity where the effect will be greatest.
7. Match internal processes and organisation to customer outcomes
Reviewing how the online and offline teams are managed and interact with customers as they travel through the journey and how this relationship is passed back and forth across teams, plays a vital role in knitting the whole optimisation strategy together. This needs careful analysis to understand where these hand-offs are taking place and the influence they have on conversion.
In many businesses this can become a complex issue as sales incentives can be involved which means some internal behaviours can inadvertently be acting against getting the sale to convert. Map these connections out carefully and ensure ecommerce teams and sales teams in branches and call centres participate and buy into the process. With this design fair systems and internal contracts for how various elements of the business are rewarded for their part in the sale.
8. Align sales reward approach
Designing a sales reward system that supports the omni-channel journey is probably the single most important task to achieve the best lead optimisation results. The key objective is to support retail customers in choosing how they browse and buy via the web, store, telephone or a combination of these. The retailer needs to support and incentivise the sales and e-commerce teams, across the channels to ensure the customer receives a seamless experience from browsing to sale.
Now, it is more important than ever that customers spend their more limited time in store most efficiently by helping them to complete their sale online at home. Reward systems need to be in place that reward staff even if the customer goes on to complete the purchase through a different channel, so staff are happy to nudge the customer along whichever is the best journey for them. Getting it right has benefits for the customer, the sales team and the business.
Benefits to customers:
Seamless interaction with the brand.
Allowing them to limit their time in store if required/preferred.
Ultimate choice and flexibility in how they browse, choose and pay for their items.
Benefits to the sales team:
More relaxed customers instore, in the knowledge they can spend their time browsing and spending time getting help with their choice.
Ability to make the sale and set the basket up digitally to give clients confidence.
Be rewarded for those sales where their help has influenced the buying decision.
Benefit to the business:
Healthy store teams able to focus on their job in safe way for them and their customers.
Happy customers able to buy in a way that they are most comfortable with.
Increased sales from time spent with customers in store most efficiently.
Hypothesis and Action Planning
With both of these perspectives in mind e.g. the role specific site features and functionality play in conversion as well as the proposition specifics then allows the development of the hypotheses of how and where to increase conversions. The hypotheses define the particular change or changes to the experience or site that will have what impact on a specific conversion objective and the rationale or insights behind the reason why this is the case.
Best practice usually defines these hypotheses as binary yes or no outcomes. For example hypotheses for a subscription based product may include: H0 – tailored comms do not influence early life engagement; H1 – tailored comms reduce churn and increase revenue during early life.
The way to prove or disprove either of these is to run a test. Structuring and forming the hypotheses, defining the approach up front and establishing the KPIs are important steps in the process and ensure the efforts taken will lead to reliable and credible outcomes. Hypotheses and the associated test plans should be developed collaboratively across the business and signed off before any testing starts. This is crucial to secure the likely ongoing development or investment required to implement and productionise the changes.
*Example Hypothesis Test Framework.*
There are a number of frameworks suitable to prioritise where to spend an optimisation budget, but we recommend tailoring these to suit individual business priorities and styles. This could as simple as assessing each test by its potential to improve, its importance or value and feasibility or ease of implementation. Sometimes though the criteria can include more criteria that relate to the business priorities or objectives such as the example below:
Finance: Potential to deliver worthwhile value within sensible timeframes.
Change: That is achievable around BAU without causing massive disruption or risk.
Buy-in: Of sufficient interest to help rive ongoing engagement and support of data by the business.
Future: It is repeatable and scalable.
Before running the tests establish the testing methodology by answering the following questions:
What will produce a statistically significant result?
How long should the test run for?
What kind of test is required – A/B, Split or Multivariate test.
Producing statistically significant results is obviously important to ensure accurate interpretation of the outcome of a test and is one of the main holes people will pick on if they are looking to challenge the tests. Understanding how the test will stack up as a representative sample of regular business as usual needs to be considered both at a holistic level e.g. the test will be run across10% of daily site visitors, but also might need to consider that it is also reflective of how different customer groups behave.
For example if certain groups shop with you on different days or time of day you may need to factor in when and for how long to run tests to ensure the results are representative at an aggregate as well as customer group level. Likewise, when defining the test duration, factor in the cadence and seasonal flow of customers or visitors to the site.
Depending on the nature of the business or the particular product or service in question the frequency and regularity of purchase may differ wildly from others. Significant errors can creep into a test if it is not run for a suitable amount of time to ensure it is truly representative of customers natural purchasing behaviours.
The three main ways to do testing are A/B testing, split testing and multivariate testing. Which approach you take will depend on the specific test you are running. As a general rule of thumb for the most simple tests A/B testing is perfectly suitable. As you get into more complex design and functionality changes split URL testing can be more useful where you are essentially testing the original page against a new separate page. Multivariate testing is useful for when looking at multiple changes to a page and you want to understand which combination performs best.
Interpreting the results of successful and unsuccessful tests is an important step before making wholesale changes. Successful results need careful assessment and review to validate the case or otherwise for implementation.
It is now time to revisit the business case and evaluate the true commercial potential and stack this up against a detailed understanding of the cost of implementing the change.
It is also prudent to review other hypotheses against the new learnings to see how these are impacted and where else these same learnings may apply in a wider context.
Likewise reviewing the tests that did not show a successful outcome can be a rich source of insights and may in themselves offer up new previously unconsidered hypotheses.