Spend analytics for optimising marketing expenditure
Marketers are constantly looking for innovative ways to reach out to the right customers. However, most of them end up making educated guesses about the target audience, market conditions, and possible disruptions. Guesswork may be effective to an extent, subject to the experience of the marketing team. However, it is not the best approach to accelerate the business through well-defined KPIs and metrics that you can monitor through dashboards.
True competitive advantage comes when your marketing team can predict the market dynamics and adjust the campaigns in real time for maximum impact.
This article will explain how you can detect problems with your marketing expenditure. Learn how you can use predictive analytics for marketing budget optimisation.
How to detect problems in marketing expenditure?
Studies show that only 52% of marketers use an attribution model to determine the efficiency of marketing spend. The rest do not know if they are spending at the right place. Here are a few ways you can detect problems in your market expenditure –
You run inefficient marketing campaigns
You cannot have the same metrics for every business. They differ for each marketing campaign. Your campaigns could be inefficient if the KPIs do not show continuous growth and quality leads. In general, your campaigns are inefficient if you spend more than you earn in the long run.
You waste the budget on PPC
Pay-per-click (PPC) ad campaigns that are wrongly set up could drain your monthly marketing budget in a single day. If this happens frequently, your marketing campaigns are inefficient.
You target the wrong marketing channels
You should spend most of the budget on channels that get you the most response. If your reporting does not reflect the returns correctly, you can end up wrongly distributing the budget across channels. You may overlook the channels that are potential high-growth zones.
What is predictive spend analytics?
Predictive spend analytics uses cutting-edge technologies such as artificial intelligence (AI), machine learning (ML), predictive modelling, data mining, and other statistical methods. This helps forecast customer behaviour, trends, and activities based on past and present data analysis.
These analytics strengthen your marketing efforts so that you can respond to market developments more strategically. You can use predictive analytics for –
- Factors that affect customer behaviour and buying decisions.
- Customer’s buying journey.
- Bidding patterns.
- Forecasting sales and designing marketing strategies.
How does predictive spend analytics optimise marketing expenditure?
According to a leading management consultancy and research firm, marketing budgets have increased from 6.4% to 9.5% in 2022. Here is how predictive analytics can help businesses use this money wisely –
Predict how the marketing strategy will work in the future
Accurate data will make your marketing strategy sharp and will generate maximum returns. You will have access to high-quality data for informed marketing decisions and focused campaigns.
Manage, adjust, and optimise the marketing budget
Know where you focus and spend your money. Identify the right marketing channels and the time of day when you should spend more. Use marketing budget forecast to pinpoint areas for adjustment. You can accurately project sales, revenue, and expenses and thus manage the marketing budget efficiently.
Adapt to the latest marketing trends
Optimise your marketing spend according to the latest trends to improve the ROI and customer retention and experience. By knowing the market trends, you can plan the campaigns better and stay ahead of the competition.
Use customer data for marketing budget optimisation
If you access and interpret the customer data properly, you can maximise the returns on the marketing spend. Predictive analytics can reveal everything from product usage to buying behaviour with high accuracy. You do not waste money on irrelevant ad positioning and useless communication.
Manage the marketing spend across platforms
Fine-tune the budget allocation across platforms and focus on areas you can fully control the targeting and cost. Pay close attention to which platforms are working and which ones are not. For example, a travel business may get higher returns by investing in Facebook and Instagram ads rather than Twitter or LinkedIn.
Spend analytics best practices
Managing the spend analytics can be complex, and these best practices will help you navigate through it for maximum benefits –
Define specific objectives
To get maximum benefits out of your marketing campaigns, you must align your strategy with the business objectives. You can pull data from internal systems, social media, and third-party platforms for effective predictive analytics. An example of a specific objective could be to identify those between ages 35 and 40 in a particular city who are most likely to purchase your products or services.
Setup a team with clear goals
Before spending on marketing, put together an effective team that is on the same page as you and understands the objectives. Transparency among teams is not only great for collaboration but also an effective feedback loop within the company.
Plan for disruption
Your predictive analysis model must consider unwanted events that can cause disruptions. The Covid-19 was one such disruption that no one anticipated. The spend analytics should learn from every disruption and evolve when needed.
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How can Infosys BPM help?
Spend analytics is the key to holistic business transformation. Infosys BPM helps businesses that do not have an end-to-end view of their spend. The businesses may lack predictive analytics and thus not adapt to changing market conditions. This is where technologies such as AI, ML, and analytics help them optimise the expenditure.
Read more about spend analytics solution at Infosys BPM.