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Identifying ideal leads and the world of marketing and sales

Identifying ideal leads and the world of marketing and sales

Categories
Ecommerce

Before understanding the complex mechanism of MQL, SQL and how they work it is paramount to understand what a lead is. A lead is essentially a potential consumer who has shown interest in one or other form of promotion. The marketing and sales team are pillars of any organization as they analyze and covert leads into potential buyers. The process of converting a lead to a consumer is a process and often leads to differences between the sales and marketing teams.

Most of the quarrels between sales and marketing revolve around leads. Around 61% of B2B marketers send all their leads to the sales, however only 21 % are qualified. The leads covered by the marketing team are the MQLs(Marketing Qualified Leads) while the leads covered by the sales team are the SQL(Sales Qualified Leads). The marketing team analyses a lead(MQL), if the MQL qualifies as a potential customer, it is forwarded to the sales team as an SQL. While marketing teams are found forwarding irrelevant or dis-interested leads, sales team on the other hand fails to capitalize on a certain lead and tend to ignore around half of the marketing leads.

While there are a number of influencing factors to help speed up the process of transition from an MQL to SQL and eventually a consumer, keeping note of small things could do wonders and bring unexpected boost. The image below shows a few influencing factors and a lead scoring system according to a study from SnapApp:

Lead Scoring is an essential if you want your business to grow. The scoring helps the lead team avoid bothering leads who are not ready to turn into customers yet. It helps in identifying the leads which need attention from the marketing team and helps the sales team identify leads who are ready to buy.

It’s evident that the transition from MQL and SQL is time sensitive. Thorough study and analysis of the buyers or visitors’ journey and qualification cycle could massively help a sales team. Intense auditing and scrutiny of MQLs by the marketing team could also increase efficiency and success rates. Knowledge about the target markets, profiles of existing and potential customers and their behaviours should be updated and analysed regularly. A sync between the sales team and marketing team could lead to better strategy and growth.

Track your Customer Purchases to drive more sales

Track your Customer Purchases to drive more sales

Categories
Ecommerce

Customer focus is one of the most important priorities today especially with so much of competence and brands overpowering each other to vouch for customer attention. Most retailers today are highly bent towards gaining new customers but what they forget in the hindsight is to take care of their already existing customers and in the bargain they even loose out on new as well as old customers. It is highly important for retailers to go through the past history of their customers in order to understand them better. The data generated from the past sales can help form a strategy that will help to increase the revenue. There are several methods through which one can analyze customer data, let us understand them:

Customer Order history

These are the list of orders, a customer has ordered in the past, it includes items they have purchased and constantly purchased. The history will also show, the amount they have spent on each of their purchases. It also consists of information when they bought the items. Suppose, some items were bought frequently over some festivals or holidays so it gives the data.
The point of sale system, is a robust POS system that allows browsing different data points, it includes take from customer to individual products.

Take Insights from previous purchases

Order histories are meant for the record for customers as well as brands. The brands can easily make use of the data available; let us look at some trends:

  1. Dates – the data denotes the specific time of the month, the particular item was purchased. This data will help brands to formulate selling strategy offering same goods to customers online or through email with discount options or other benefits.
  2. Products – the brands get an idea of how these products are performing with consistent purchase happening. They get information, if customers constantly buy some items together always.
  3. Customers – With this data, brands know if customers are buying certain items at one particular time. They come to know repeated buyers and hence they will formulate the strategies accordingly to formulate the customer into buying process.
  4. Upselling – If the customers are well known to your brands and are accustomed to, then they will frequently buy items from you. Brands need to upsell hence make opportunities for buyers to buy from them. For this, brands can filter the product history, identifying the customers who bought the dress, giving a follow up marketing email feature will help to entice them into buying.
  5. Personal Messages – since the brands know, what the customer bought and what their order history looks like, they can now tailor personal messages to brands.
  6. Promotions – the customer demographic data is useful for targeting the audiences on paid social advertisements and the other promotions.

Improving the Customer Experience

Order history customer data, helps the brands to improve the customer experiences. If the customer is making continuous purchases and suddenly stops, it is time for brands to have a look over it and give customer the precious momentum to get back to the brand. Enhancing their experience with the brand can do this, the motto here is to keep your customers satisfied and give them good value for money. Given below are some of the things the brands can follow:

  1. Sending personal email messages, this includes including a coupon code.
  2. Offering free samples or small gift as an appreciation for purchases made.
  3. Giving customers exclusive discounts and special deals, for this they will feel valued and may buy something extra.

Order Histories make better decisions

Customers are always focused into buying but they are always looking for the best customer experience from brands. Order histories are one such tools that helps the brands to form a blue print about the customers and make high decisions about making sales. This includes several things like keeping the inventory accurate; maintain the stores shelves well, in short giving the customers every chance to be happy. Brands should completely discontinue keeping the products that has no sales, sometimes look over at them may be a big turn off because of the bad experience a customer might have had.

Make the most of Customer Data

Customer data is a precious gem that the brands posses hence make good use of them. The order histories are good starting points and help track customers, which, what, why and how they are doing a particular purchase.

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